Archived Course Catalog for Academic Year 2017 2018
Degree Completion Requirements for AY2017/2018
The OIST Graduate School offers an integrated doctoral program leading to the degree of Doctor of Philosophy (PhD). The degree of PhD is a research postgraduate degree. Such a degree shall be awarded to a candidate who
- meets admission requirements and receives and accepts an offer of admission, and is registered as a full-time PhD student for a minimum of three years and not more than ten years; and
- satisfactorily completes prescribed work amounting to at least 30 points (20 from courses, 10 from research work) or alternatively, has obtained the equivalent number of credits based on prior study; and
- presents a successful thesis representing the result of the candidates research which should constitute an original contribution to knowledge and contain material worthy of publication; and
- satisfies the examiners in an oral examination in matters relevant to the subject of the thesis.
Note 1: coursework credits based on prior study can be waived up to a maximum of 10 elective credits to recognise relevant prior learning, at the advice of the mentor and with approval of the graduate school. This is not a guarantee that such waiver will be made, in full or part. The amount of waiver due to prior relevant coursework is at the discretion of the mentor.
Note 2: a published paper or manuscript ready for publication from the research work presented in the thesis shall be submitted with the thesis to denote that the "material is worthy of publication". Students in AY2016 cohort and onwards must provide evidence that a paper has been submitted, if none has been published.
Note 3: after successful examination of the written thesis, a thesis defence is conducted before two external examiners on-site in an oral exam. A public presentation of the thesis is required, and takes place immediately preceding the closed examination.
Note 4: Examination and final versions of the thesis are submitted only as PDF files. All theses are published online in the OIST Institutional Repository. Partial embargo periods are available by negotiation.
Courses delivered AY2017/2018
A101 Adaptive Systems
This course aims to provide common mathematical frameworks for adaptation at different scales and to link them with biological reality of control, learning, and evolution. We will look at different classes of adaptation problems using real-world examples of robot control, web searching, gene analysis, imaging, and visual receptive fields.
- Introduction: variety of learning and adaptation
- Probability theory: entropy, information, Bayes theorem
- Pattern classification
- Function approximation
- Kernel methods
- Clustering, Mixture Gaussian, EM algorithm
- Principal Component Analysis, Self-organizing map
- Graphical models, Belief propagation
- Sampling methods, Genetic algorithms
- Kalman filter, Particle filter
- Reinforcement learning, Dynamic programming
- Decision theory, Game theory
- Multiple agents, Evolutionary stable strategies
- Communication and cooperation
- Presentation and discussion
Assumes good knowledge of statistics and ability to look at biological problems in a mathematical way.
OIST courses to complete beforehand: B07 Statistical Methods
A102 Mathematical Methods of Natural Sciences
Course Coordinator: Jonathan Miller
This course develops advanced mathematical techniques for application in the natural sciences. Particular emphasis will be placed on analytical and numerical, exact and approximate methods, for calculation of physical quantities. Examples and applications will be drawn from a variety of fields. The course will stress calculational approaches rather than rigorous proofs. There will be a heavy emphasis on analytic calculation skills, which will be developed via problem sets.
- Complex Analysis I: Introduction to complex analysis: analytic functions.
- Complex Analysis II: Cauchy Theorem and contour integration.
- Complex Analysis III: Numerical methods in complex analysis.
- Linear algebra I: Advanced eigenvalues and eigenvectors.
- Linear algebra II: Numerical methods.
- Ordinary differential/difference equations (ODDE) I: Properties and exact solutions.
- ODDE II: Approximate solutions.
- ODDE III: Numerical solution.
- Asymptotic expansion of sums and integrals I: elementary methods.
- Asymptotic expansion of sums and integrals II: steepest descents.
- Perturbation methods.
- Boundary layer theory.
- WKB theory.
- Vector fieldsStokes theorem.
- Green's functions.
A103 Stochastic Processes with Applications
This course will present a broad introduction to stochastic processes. The main focus will be on their application to a variety of modeling situations and on numerical simulations, rather than on the mathematical formalism. After a brief resume of the main concept in probability theory, we will explain what stochastic processes are and the concept of stochastic trajectory. We will then broadly classify stochastic processes (discrete/continuous time and space, Markov property, forward and backward dynamics). The rest of the course is devoted to the most commonly used types of stochastic processes: Markov chains, Master Equations, Langevin/Fokker-Planck equations. For each process, we will review the main applications in physics, biology, and neuroscience, and discuss the simplest algorithms to simulate them on a computer. The course will include “hands-on” sessions in which the students will write their own Python code (based on a template) to simulate stochastic processes, aided by the instructor. These numerical simulations will be finalized as homework and will constitute the main evaluation of the course.
1) Basic concepts of probability theory. Discrete and continuous distributions, main properties. Moments and generating functions. Random number generators.
2) Definition of a stochastic process and classification of stochastic processes. Markov chains. Concept of ergodicity. Branching processes and Wright-Fisher model in population genetics.
3) Master equations, main properties and techniques of solution. Gillespie algorithm. Stochastic chemical kinetics.
4) Fokker-Planck equations and Langevin equations. Main methods of solution. Simulation schemes for Langevin equations. Random walks and colloidal particles in physics.
5) First passage-time problems. Concept of absorbing state and main methods of solution. First passage times in integrate-and-fire neurons.
• Basic calculus: students should be able to calculate integrals, know what a Fourier transform is, and solve simple differential equations.
• Basic probability theory: students should be familiar with basic concepts in probability theory, e.g. discrete and continuous distributions, random variables, conditional probabilities, mean and
variance, correlations. A resume will be made at the beginning of the course.
• Scientific programming: the students are expected to be already able to write, for example, a program to integrate a differential equation numerically via the Euler scheme and plot the results. Python is the standard language for the course. The students are required to install the Jupiter notebook system and bring their own laptop for the hands-on sessions.
A202 Fluid Dynamics
This course introduces students to the fundamental laws that characterize fluids at rest and in motion. The equations for the conservation of mass, for momentum balance, and for conservation of energy are analyzed in control volume and, to some extent, in differential form. Students will learn to select appropriate models and solution procedures for a variety of problems. Flow phenomena that occur in actual flow situations are also illustrated, so that students will learn to assess the strengths and limitations of the models and methods.
- Introduction (Background, Definitions, general concepts, etc)
- Fluid Statics (Hydrostatic balance, pressure forces on objects)
- Fluid Statics (Effects of constant acceleration or rotation)
- Bernoulli Equation (Use of Newton's second law)
- Bernoulli Equation (Pressure and its measurement)
- Fluid Kinematics (Description of velocity field)
- Fluid Kinematics (Control volume, system representations)
- Fluid Kinematics (Reynolds transport theorem)
- Control volume Analysis (Conservation laws)
- Control volume Analysis (Many applications)
- Dimensional Analysis (Dynamic similarity)
- Dimensional Analysis (Pi theorem, Applications)
- Flow in Pipes, Ducts, Etc. (Laminar and turbulent pipe flow, etc)
- Flow Around Objects (Boundary layers & potential flow, etc)
- Compressible Flow (Mach number, sound speed, etc)
A205 Quantum Field Theory
Course Coordinator: Shinobu Hikami
This course covers quantum electrodynamics and chromodynamics. Topics include canonical quantization, Feynman diagrams, spinors, gauge invariance, path integrals, identical particles and second quantization, ultraviolet and infrared divergences, renormalization and applications to the quantum theory of the weak and gravitational forces, spontaneous symmetry breaking and Goldstone bosons, chiral anomalies, effective field theory, non-Abelian gauge theories, the Higgs mechanism, and an introduction to the standard model, quantum chromodynamics and grand unification.
- An electron in a uniform electromagnetic field: Landau levels
- Canonical Quantization
- Antiparticles
- Particle decay
- Feynman rules and the S-matrix
- Weyl and Dirac spinors
- Gauge Theories
- Quantization of the electromagnetic field
- Symmetry breaking
- Path integrals
- Aharonov-Bohm effect
- Renormalization
- Quantum chromodynamics
- Nuclear forces and Gravity
- Field unification
A206 Analog Electronics
A practical course to train students in the design and construction of analog electronic circuits, based on the classic text The Art of Electronics. Conceptual understanding of the key elements of analog circuits will be reinforced by significant project work in the electronics workshop.
- Passive components. Current and voltage sources, Thevenin and Norton equivalent circuits. Diodes. (Ebers Moll equation)
- The bipolar transistor, transconductance and its use in making efficient current and voltage sources.
- Common emitter, common base, amplifiers. Differential amplifiers, current mirrors.
- Push pull and other outputs, as well as some other useful circuits. Miller effect.
- Thermal behavior of transistors; circuit temperature stability.
- Field effect transistors and analog switches.
- Operational Amplifiers and basic op amp circuits.
- Negative feedback.
- Sample and hold, track and hold, circuits. Further applications of op amps.
- Filters
- Voltage Regulators
- Noise, noise reduction, transmission lines, grounding, shielding,
- Lock in amplifiers.
- Instrumentation amplifiers.
- Analog to Digital conversion.
A207 Nanotechnology
Course Coordinator: Mukhles Ibrahim Sowwan
This course covers the Nanotechnology revolution in science and engineering that is leading to novel ideas about the way materials, devices, and systems are designed, made and used in different applications. We cover the underlying principles of the multidisciplinary and very diverse field of nanotechnology, and introduce the concepts and scientific principles relevant at the nanometer scale. Then we provide a comprehensive discussion of the nanomaterials, including characterization techniques and the effect of size on their structural, physical, and chemical properties and stability. In addition we discuss the current and future applications of Nanotechnology in different fields such as materials engineering, medicine, electronics, and clean energy.
1, 2. Introduction to Nanotechnology and its applications (2 lectures)
History, State of the art nanotechnology, applications in different fields
3, 4. Surface imaging and visualizations (2 lectures)
SPM, SEM, TEM
5, 6. Conventional Nanofabrication (2 lectures)
Microfabrication, e-beam lithography, photolithography, micro and nanoelectronics
7, 8. Non-conventional nanofabrication (2 lectures)
Nanoimprint lithography, bottom top fabrication
9 – 13. Nanomaterials: Synthesis, properties and application (5 lectures)
Nanoparticles, nanorods, nanocrystals, nanobiomaterials , nanostructured thin films
14, 15. Nanosystems and self-assembly (2 lectures)
Self assembly of hybrid systems, bioorganic/inorganic inspired nanodevices
A208 Bioorganic Chemistry
This course covers essential concepts and recent advances in the design and synthesis of functional molecules used for understanding and controlling biological systems. Topics of this course include design and synthesis of small organic molecules, organic reactions, methods for controlling reaction pathways, asymmetric synthesis, mechanisms of catalysis and molecular recognition, and creation of designer proteins and peptides.
- Methods of chemical transformations to access designer molecules
- Strategies for the development of new reaction methods including stereoselective reaction methods
- Asymmetric reactions and asymmetric catalysis
- Catalytic enantioselective reactions: Carbon-carbon bond forming reactions
- Catalytic enantioselective reactions: hydrolysis, reduction, dynamic kinetic resolutions, etc.
- Design and synthesis of functional molecules
- Chemical mechanisms of bioactive molecules including chemistry of enzyme inhibitors
- Molecular recognition and non-covalent bond interactions
- Enzyme catalysis and catalytic mechanisms
- Enzyme catalysis and small organic molecule catalysis
- Enzyme kinetics and kinetics of non-enzymatic reactions
- Strategies for the development of new designer catalysts
- Methods in identification and characterization of organic molecules
- Strategies for the development of designer functional proteins and peptides
- Chemical reactions for protein labeling; chemical reactions in the presence of biomolecules
A209 Ultrafast Spectroscopy
This course will be an introductory graduate level course to initiate students into the techniques of ultrafast spectroscopy. They will be introduced to the basic concepts underlying sub-picosecond phenomena in nature (ultrafast chemical processes, femtosecond electron dynamics in materials, etc.) and the tools used to study such phenomena (pump-probe spectroscopy, Terahertz Time Domain Spectroscopy, etc.).
- Introduction, History and Development:
- Basic Concepts
- Understanding Ultrafast Pulses: Spectrum, Fourier Transform, Uncertainty Principle, wavelength, repetition rate
- Understanding Ultrafast Pulses & Capabilities: Time Resolution, Nonlinearities,
- Ultrafast pulse measurement: Spectrum, Phase, Amplitude, Intensity
- Ultrafast pulse measurement: AutoCorrelation, FROG, SPIDER
- Ultrafast Techniques: Pump Probe, Four-Wave Mixing, or others.
- Ultrafast Techniques: Time Resolved Fluorescence, Up-converstion, or others.
- Ultrafast Techniques: THz-TDS, Higher Harmonic Generation, or others.
- Ultrafast Techniques: Single Shot Measurements, etc.
- Applications: e.g. Condensed Matter Physics
- Applications: e.g. Chemistry and Materials Science
- Applications: e.g. Biology
A210 Advanced Quantum Mechanics
Advanced course in Quantum Mechanics, based on recent theoretical and experimental advances. Evolution in Hilbert space and quantum bits; conditional quantum dynamics; quantum simulations; quantum Fourier transform and quantum search algorithms; ion-trap and NMR experiments; quantum noise and master equations; Hilbert space distances; Von Neumann entropy; Holevo bound; entanglement as a physical resource; quantum cryptography; lab: quantum eraser, interaction free measurement.
- Quantum Mechanics: Mathematical Framework
- Quantum Mechanical Postulates
- Quantum Measurements
- Quantum Algorithms
- Quantum Computing: Physical Realisations
- Quantum Noise
- Entropy and Information
- Quantum Statistical Mechanics
- Quantum Information Theory
A211 Advances in Atomic Physics
Course Coordinator: Síle Nic Chormaic
Description:
Advanced level course in atomic physics. Progress in laser control of atoms has led to the creation of Bose-Einstein condensates, ultrafast time and frequency standards and the ability to develop quantum technologies. In this course we will cover the essentials of atomic physics including resonance phenomena, atoms in electric and magnetic fields, and light-matter interactions. This leads to topics relevant in current research such as laser cooling and trapping.
Aim:
To introduce students to recent advances in atomic physics
Course Content:
Early atomic physics
The hydrogen atom and atomic transitions
Helium and the alkali atoms
LS coupling
Hyperfine structure
Atom interactions with radiation
Laser spectroscopy
Laser cooling and trapping
Bose-Einstein condensation
Fermionic quantum Gases
Atom interferometry
Ion traps
Practical elements: Laser spectroscopy
Practical elements: Laser cooling of Rb
Applications: Quantum computing
Practical Exercises : presentations, laboratory exercises on light-matter interactions
Course Type:
Elective
Credits:
2
Assessment:
Continuous Assessment: 40%, Midterm Exams: 2 x 15%, Final Exam, 30%.
Text Book:
No single textbook will be used during this course.
Reference Book:
Advances in Atomic Physics: An Overview by Cl. Cohen-Tannoudji and D. Guéry-Odelin (2011) World Scientific
Atomic Physics by C.J. Foot (2013) Oxford
Introductory Quantum Optics by C.C. Gerry and P. L. Knight (2005) Cambridge
A212 Microfluidics
Course Coordinator: Amy Shen
The interface between engineering and miniaturization is among the most intriguing and active areas of inquiry in modern technology. The aim of this course is to illuminate and explore microfluidics as an interdisciplinary research area, with an emphasis on emerging microfluidics disciplines, including molecular assembly to bulk and device level scales, with applications in novel materials synthesis, bio-microtechnology and nanotechnology.
The course will begin by highlighting important fundamental aspects of fluid mechanics, scaling laws and flow transport at small length scales. We will examine the capillary-driven, pressure-driven, and electro-kinetic based microfluidics. We will also cover multi-phase flow, droplet-based microfluidics in microfluidics. This course will also illustrate standard microfabrication techniques, micro-mixing and pumping systems.
- Introduction to microfluidics; Scaling analysis
- Low Reynolds number flows
- Pressure-driven microfluidics
- Capillary-driven microfluidics
- Microfabrication
- Diffusion in microfluidics
- Mixing in microfluidics
- Droplet microfluidics and 2-phase flows
- Bio-MEMs
A213 Inorganic Electrochemistry
In this course, students will learn basic principles of electrochemistry with a particular focus on redox behavior of transition metals including metalloproteins. Modern research in application of transition metal complexes for renewable energy storage and production will be highlighted and discussed in detail, including metal-catalyzed water oxidation, proton reduction and CO2 reduction processes. The course will provide practical training in voltammetric techniques and spectroelectrochemistry, and analysis and simulation of cyclic voltammetry data.
- Basic aspects of electrochemistry
- Electrochemical instrumentation
- Cyclic voltammetry: Reversible, irreversible and quasireversible processes
- Cyclic voltammetry: Effect of coupled chemical reactions; Digital simulation of cyclic voltammograms
- Bulk electrolysis and pulsed voltammetric techniques
- Hydrodynamic techniques: application for studying reaction intermediates and mechanisms.
- Electrochemical behavior of transition metal complexes.
- Redox-active metalloproteins
- Redox-induced structural reorganization of metal complexes
- Electrocatalysis by transition metals for renewable energy production and storage: water splitting to O2and H2
- Transition metal-catalyzed electroreduction of CO2 and dehydrogenation of formic acid and alcohols: application for hydrogen storage
- Immobilization of metal catalysts on electrode surface
- Photoelectrochemistry
- Application of electrochemical processes in chemical industry
A214 Nucleic Acid Chemistry and Engineering
Course Coordinator: Yohei Yokobayashi
In this course, students will learn basic principles of nucleic acid chemistry and engineering through lectures and discussions. The students will then use the basic knowledge to deepen their understanding of the current research in the field of nucleic acid chemistry and engineering. Finally, the students will design, construct, and characterize functional nucleic acids in the laboratory while learning basic experimental skills to manipulate nucleic acids.
Basic nucleic acid chemistry (3 hr)
- Structure (DNA, RNA, unnatural nucleic acids, secondary/tertiary structures)
- Thermodynamics (hybridization)
Synthesis of nucleic acids (4.5 hr)
- Chemical synthesis (solid phase synthesis)
- Biochemical synthesis (PCR, in vitro transcription, gene synthesis, biological synthesis, etc.)
Analysis of nucleic acids (4.5 hr)
- Chemical analysis (UV, electrophoresis, CD, nuclease probing, SHAPE, etc.)
- Sequence analysis (Sanger, Illumina, PacBio, nanopore, etc.)
Nucleic Acid Engineering (12 hr)
- Synthetic nucleic acids
- Unnatural bases and backbones
- Self-assembly, materials
- Nucleic acid amplification and detection
- Therapeutics
- Aptamers
- Catalytic nucleic acids
- In vitro selection, in vitro evolution
- Molecular computation
- Biological nucleic acids
- Riboswitches
- Ribozymes
Laboratory: Design, construction, and characterization of functional nucleic acids (12-16 hr labs)
A215 Advanced Experimental Chemistry
Course Coordinator: Ye Zhang
Materials chemistry is emerging as an interdisciplinary field that involves knowledge from diverse science and engineering research fields. The recent public attention and enthusiasm on nanoscience and nanotechnology not only underscores the importance of interdisciplinary research, but also highlights the promises of materials chemistry. The development of modern chemistry allows chemists to precisely control the three-dimension arrangement of many atoms for developing novel materials. In this laboratory course, we will discuss the development and applications of five kinds of materials and synthesize them using classical chemical reactions through modern techniques. The course is a combination of basic theoretical study, and hands on experimental practice, following with further discussions on modern applications and self-designed possible applications as the after class challenge. The course is designed to be accessible to students from a wide range of educational backgrounds.
Experiment 1: Temperature-sensitive Polymeric Hydrogel
Experiment 2: Magnetic Nanoparticles/Ferrofluids
Experiment 3: Lyotropic Liquid Crystals
Experiment 4: Gold Nanoparticles
Experiment 5: Supramolecular Nanofibers/Hydrogels
(Each experiment runs up to 10 hours over 2 weeks)
A216 Quantum Mechanics I
A217 Quantum Mechanics 2
This is a two-term graduate course that covers most of the essential topics of modern nonrelativistic quantum mechanics. The course is primarily intended for graduate students with background in Physics.
Quantum Mechanics I
- Early crisis of classical mechanics and motivations for a new approach in physics: black body radiation and “ultraviolet catastrophe”, Plank’s hypothesis. Einstein’s explanation of photoelectric effect. Bohr’s model of hydrogen atom.
- Brief review of analytical mechanics: Newtonian mechanics and conservation laws, constrains and Lagrange reformulation of classical mechanics. Hamiltonian formalism. Poisson brackets and canonical transformations. The Hamilton-Jacoby equation.
- Brief review of classical electrodynamics: Maxwell equations and boundary conditions, effect of continuous medium, propagation of electromagnetic waves. Ray optics and eikonal approximation. Charged particle in electric and magnetic fields.
- Motivations for postulates of quantum mechanics: Young’s double-slit experiment. de Broglie’s hypothesis of matter waves.
- Bra-ket formalism, Hilbert space, operators, and their matrix representation. Postulates of quantum mechanics. General uncertainty relation.
- Canonical transformation in quantum mechanics as a main approach to describe motion of a physical system. Translation in space and operator of momentum. Coordinate and momentum representations. Coordinate-momentum uncertainty relation and the Standard Quantum Limit.
- Time-evolution operator. Energy-time uncertainty relation. The Schrodinger equation of motion and continuity equation. The Heisenberg picture and equation of motion for operators.
- Some exactly solvable problems in wave mechanics: particle in free space and motion of the Gaussian packet, particle in the box, linear potential, potential barriers and tunneling. Quantum harmonic oscillator: two approaches in solving the problem, coherent and squeezed states of the quantum harmonic oscillator.
- The WKB approximation. Feynman’s path integral and classical limit of the quantum mechanics.
- Quantum particle in static electric and magnetic fields. Gauge transformation and the Aharonov-Bohm effect. Macroscopic quantum coherence and the Josephson effect. Charged particle in the uniform magnetic field: Landau states and their degeneracy. The Quantum Hall effect.
- Rotations in space and operator of angular momentum. Orbital and spin angular momentums. Coordinate representation of orbital angular momentum. Spherical harmonics.
- The Schrodinger equation of motion in 2D and 3D. Particle in central potential: 2D and 3D rigid rotators, particle in a spherical box, 3D quantum harmonic oscillator, Hydrogen atom and emission spectrum.
- Scattering and diffraction of a quantum particle: Born approximation, expansion into the partial waves.
- Spin-1/2 particle. Stern-Gerlach experiment. Matrix representation of spin-1/2 states and Pauli matrices. Spin-1/2 particle in the uniform magnetic field.
- Spinor. Addition of angular momentums. Spin-orbit interaction.
Quantum Mechanics 2
1. N-particle systems. Indistinguishable particles and Pauli exclusion principle. System of spin-1/2 particles and exchange interaction. Introduction to second quatization methods.
2. Symmetries in quantum mechanics. Invariance under unitary transformations and conservation laws. Space inversion symmetry and parity. Lattice symmetry: Bloch waves and energy bands. Time reversal symmetry.
3. Approximation methods in quantum mechanics: variational methods, time-independent perturbation theory. Time-independent perturbation theory in case of degenerate states. Selection rules for orbital angular momentum.
4. Hydrogen atom revisited: fine structure and hyperfine splitting.
5. Hydrogen atom in static electric and magnetic fields: quadratic and linear Stark effects, Zeeman splitting and Paschen-Back effect.
6. Time-dependent perturbation theory. Dyson series for the time-evolution operator. Transitions under time-dependent perturbations: adiabatic and sudden perturbations.
7. Harmonic perturbation and interaction of quantum particle with electromagnetic field. The Fermi’s golden rule. Stimulated emission and absorption of electro-magnetic waves by a quantum particle.
8. Exactly solvable time-dependent problem: two-level system approximation and the Rabi oscillations.
9. Introduction to the quantum electrodynamics: quantization of electro-magnetic field. Photons and vacuum fluctuations of electro-magnetic field.
10. Hydrogen atom revisited (again): the Lamb shift.
11. Interaction of quantum particle with electromagnetic field revisited: beyond semi-classical description. Spontaneous emission. The Einstein coefficients.
12. Some topics of modern quantum mechanics: cavity QED and Janes-Cummings Hamiltonian. Implications for qubits.
13. Introduction to quantum mechanical statistics. Density matrix formalism. Pure and mixed ensembles of particles. Description of a system of noninteracting particles.
14. Dynamics of an open quantum system and dephasing. Density matrix approach and the master equation. Von Neumann’s postulate of quantum measurements.
A218 Condensed Matter
Condensed matter physics is both old-fashioned (originating from solid state physics in 1950’s or even metal physics in 1920’s) and also new style (with emphasis on collective behaviour, symmetry, and topological conditions). Over the past century, this sub-field of physics has grown to a monstrous size with various ramifications such that any perspective offered would always be partial and biased. Here this class will be served at the introduction level, and at a few places, I will try to demonstrate how to evolve from fundamental concepts to perspectives of advanced topics. Nevertheless, the first half of this course is built on the single particle picture and is of mean field nature. The second half starts to introduce a few examples of electron correlation. More specialized fields, such as spintronics and topological states and excitations, will not be covered here.
- Introduction: the change of perspective and paradigms in condensed matter physics.
- Phase transitions, critical phenomena, and mean field approach.
- Renormalization approach, universality classes, quantum phase transition.
- Crystals, symmetry, space groups.
- Phonons. X-ray and neutron diffuse scattering.
- Amorphous materials, glass, correlation function, quasi-crystals.
- Itinerant electrons, band structure, Fermiology, dHvA techniques, resistivity.
- Electronic excitations, dynamic form factor, inelastic scattering.
- Superconductivity, BCS vs BEC in solids.
- Exchange interaction, static magnetic orders magnetic space group.
- Magnetism: dimension, geometry, and frustration. Disordered spin states.
- Soft condensed matter: liquids, liquid crystals, and mesoscopic physics.
- Perspective of advanced topics.
Students are required to have basic understanding of quantum mechanics (e.g., A216 QM I and A217 QM II), and basic concepts of statistics.
A219 General Relativity
We begin by introducing tensors in non-relativistic physics. We then give an overview of Special Relativity, and discuss the special nature of gravity as an “inertial force”. With this motivation, we develop the differential geometry necessary to describe curved spacetime and the geodesic motion of free-falling particles. We then proceed to Einstein’s field equations, which we analyze in the Newtonian limit and in the linearized limit (gravitational waves). Finally, we study two iconic solutions to the field equations: the Schwarzschild black hole and Friedman-Robertson-Walker cosmology. We will use Sean Carroll’s textbook as the main reference, but we will not follow it strictly.
This is an alternating years course.
1. Tensors in 3d: moment of inertia and magnetic field
2. Special Relativity in 3d language
3. Special Relativity in 4d language: Minkowski spacetime
4. Gravity as an inertial force: the equivalence principle
5. Curved spacetime: metric and Christoffel symbols
6. Geodesic motion: Newtonian limit, redshift, deflection of light
7. Curved spacetime: The Riemann tensor and its components
8. The Einstein field equations and their Newtonian limit
9. Linearized limit and gravitational waves
10. The Schwarzschild black hole
11. More on the Schwarzschild metric: precession of planets, black hole thermodynamics
12. Friedmann-Robertson-Walker cosmology
Prerequisites: Maxwell’s equations in differential form. Solving Maxwell’s equations to obtain electromagnetic waves. Linear algebra of vectors and matrices.
A273 Ultracold Quantum Gases
The course will start out by introducing the fundamental ideas for cooling and trapping ultracold atoms and review the quantum mechanical framework that underlies the description of interacting matter waves in the ultracold regime. This will introduce the idea of degenerate Bose and Fermi gases, and in particular the concept of Bose-Einstein condensation.
After this the main properties of Bose-Einstein condensates will be discussed, including coherence and superfluidity, and for Fermi gases the physics of the BCS transition will be introduced. Conceptually important developments such as optical lattices, Feshbach resonances, artificial gauge fields and others will be explained in detail as well. New developments in the area of strongly correlated gases will be introduced and applications of cold atoms in quantum information or quantum metrology provide the final part of the course.
The course will mostly focus on the theoretical description of ultracold quantum gases, but regularly discuss experimental developments, which go with these.
Aim:
The course introduces the students to the field of ultracold quantum gases. The lectures are combined with a weekly journal club, where original publications related to the lecture are discussed. Students will learn some fundamental concepts and techniques used in ultracold atoms research and obtain an overview over the many directions this diverse field is developing into. At the end of the course the students should be able to read current scientific literature and discuss work with researchers in the area. Since the area of ultracold quantum gases has connections to many other fields of physics, especially condensed matter and optics, students will be able to pick up aspects of these as well.
1. Ultracold atomic gases: cooling and trapping
2. Bose-Einstein condensation and Fermi degeneracy in ideal gases
3. Interacting Bose-Einstein condensates: Gross-Pitaevskii equation.
4. Dynamics of Bose-Einstein condensates. Expanding and oscillating condensates.
5. Elementary excitations. Bogoliubov-De Gennes equations.
6. Two-dimensional Bose gases. Kosterlitz-Thouless transition.
7. Vortices and Superfluidity
8. One-dimensional systems: quasi-condensates and solitons
9. Strongly interacting 1D Bose gases. Impenetrable bosons.
10. Degenerate Fermi gases: BEC and BCS transitions
11. Optical lattices
12. Artificial Gauge fields
13. Applications in quantum information and metrology
While the fundamental concepts of atomic physics and quantum mechanics that are required will be reviewed in the beginning of the course, basic prior knowledge of quantum mechanics is required (e.g. A216 & A217).
Companion course to A211 Advances in Atomic Physics
A303 Developmental Biology
Course Coordinator: Ichiro Masai
This course introduces fundamental principles and key concepts in the developmental processes of animal organisms, by focusing on Drosophila embryonic development and vertebrate neural development as models, and will facilitate graduate students to reach a professional level of understanding of developmental biology. Furthermore, genetic tools for live imaging of fluorescence-labeled cells using Drosophila and zebrafish embryos will be introduced as practical exercises. The course also includes debate on specific topics in developmental biology by students and a writing exercise of mock-grant application. Some lecturers outside OIST will be invited to present particular special topics.
- Basic concepts of developmental biology, and introduction of model systems
- Development of the Drosophila embryonic body plan
- Organogenesis
- Patterning of vertebrate body plan
- Morphogenesis
- Cell fate decision in the vertebrate nervous system
- Current topics of neuronal specification and multipotency of neural stem cells
- Axon guidance, target recognition
- Synaptogenesis
- A model for neurodegeneration in Drosophila
- Debate of topics of developmental biology by students
- Debate of topics of developmental biology by students
- Debate of topics of developmental biology by students
- Genetic tools for live imaging of fluorescence-labeled cells using Drosophila
- Genetic tools for live imaging of fluorescence-labeled cells using zebrafish
A304 Evolutionary Developmental Biology
The course presents the most recent theory and techniques in evolutionary and developmental biology with an emphasis on the underlying molecular genomics. Recent advances in decoding the genomes of various animals, plants and microbes will be followed, with a discussion on comparative genomics, the evolution of transcription factors and signal transaction molecules and their relation to the evolution of the various complex body plans present through history.
- Introduction (background, general concepts, etc)
- History of animals (fossil records, phylogenic tree)
- History of animals (genomics, molecular phylogeny)
- Genetic toolkits (developmental concepts)
- Genetic toolkits (Hox complex)
- Genetic toolkits (genetic toolkits, animal design)
- Building animals (lower metazoans)
- Building animals (protostomes)
- Building animals (deuterostome and vertebrates)
- Evolution of toolkits (gene families)
- Diversification of body plans (body axis)
- Diversification of body plans (conserved and derived body plans)
- Evolution of morphological novelties
- Species diversification
- Phylum diversification
A306 Neuroethology
The course provides an understanding of the neuronal mechanisms that underlie animal behavior. We will study the neuronal mechanisms for specialized animal behaviors such as sensory processing, motor pattern generation, and learning by reading original papers, which also provide an understanding of experimental technique. The course further discusses the evolutionary strategy and the biological ideas of animal behavior and underlying neuronal mechanisms.
- Introduction (Basic Neurophysiology and neuronal circuits)
- Sensory information I: Visual and Auditory (map formation, plasticity and critical period, etc.)
- Sensory information II: Olfactory (Chemical) and other senses
- Sensory perception and integration I (Echolocation, Sound localization, etc.)
- Sensory perception and integration II (Sensory navigation, etc.)
- Motor control I (Stereotyped behavior)
- Motor control II (Central pattern generator)
- Sexually dimorphic behavior
- Learning I (Learning and memory)
- Learning II (Associative learning)
- Learning III (Sensory motor learning during development)
- Learning VI (Spatial navigation)
- Behavioral plasticity and the critical period
- Recent techniques in neuroethology
A307 Molecular Oncology and Cell Signalling
Course Coordinator: Tadashi Yamamoto
This course consists of lectures and exercises. First, students learn, through lectures, recent progress in cancer research and the mechanism of carcinogenesis based on the molecular and cellular functions of oncogenes and anti-oncogenes. Further, students will learn the relevance of signal transduction, cell cycle progression, cell adhesion, and gene regulation to tumor development and are encouraged to simulate effective methods of diagnosis and treatment of cancer. Further, through exercises, students will consider the relevance of genome sciences and systems biology to cancer research. Students are encouraged to refer to the textbook and to papers from the current literature. The course will also present special novel and important topics from year to year.
- Historical background of molecular oncology
- Viruses, chemical carcinogens, and tumor development
- RNA tumor viruses and oncogenes
- Discovery of anti-oncogenes
- Regulation of signal transduction and cell cycle progression by oncogenes and anti-oncogenes
- Roles of oncogenes and anti-oncogenes in normal physiology
- Molecular mechanisms of metastasis
- Genome, proteome, metabolome, and cancer
- Animal models of cancer
- Drug development for cancer treatment
- Cancer stem cells
- microRNA and cancer development
- Genome sciences in cancer research
- Systems biology in cancer research
A308 Epigenetics
Epigenetic regulation of gene activity is essential for development and response to environmental changes in living organisms. This course introduces fundamental principles and key concepts of epigenetics, and original research publications contributed to understanding the mechanism underlying the epigenetic phenomena will be reviewed. Lecturers from outside OIST may be invited for specific topics.
- Introduction to Epigenetics
- Histone variants and modifications
- DNA methylation
- RNA interference and small RNA
- Regulation of chromosome and chromatin structure
- Transposable elements and genome evolution I
- Transposable elements and genome evolution II
- Epigenetic regulation of development I
- Epigenetic regulation of development II
- Genome imprinting
- Dosage compensation I
- Dosage compensation II
- Epigenetic reprogramming and stem cells
- Epigenetics and disease
- Epigenomics
Requires at least B06 Cell Biology and Genetics or similar background knowledge
A310 Computational Neuroscience
Course Coordinator: Erik De Schutter
Computational neuroscience has a rich history going back to the original Hodgkin-Huxley model of the action potential and the work of Wilfrid Rall on cable theory and passive dendrites. More recently networks consisting of simple integrate-and-fire neurons have become popular. Nowadays standard simulator software exists to apply these modeling methods, which can then be used to interpret and predict experimental findings.
This course introduces some standard modeling methods with an emphasis on simulation of single neurons and synapses and an introduction to integrate-and-fire networks. Each theoretical topic is linked to one or more seminal papers that will be discussed in class. A number of simple exercises using the NEURON simulator will demonstrate single neuron and synapse modeling.
- Introduction and the NEURON simulator
- Basic concepts and the membrane equation
- Linear cable theory
- Passive dendrites
- Modeling exercises 1
- Synapses and passive synaptic integration
- Ion channels and the Hodgkin-Huxley model
- Neuronal excitability and phase space analysis
- Other ion channels
- Modeling exercises 2
- Reaction-diffusion modeling and calcium dynamics
- Nonlinear and adaptive integrate-and-fire neurons
- Neuronal populations and network modeling
- Synaptic plasticity and learning
Requires prior B03 Mathematics I, B04 Mathematics II and B05 Neurobiology or similar background knowledge.
A311 Cellular Aging and Human Longevity
Course Coordinator: Mitsuhiro Yanagida
A series of lectures and seminar (for invited lecturers) will provide basic concepts how contemporary scientists challenge the enigma of longevity and lifespan through diverse methodology. The subjects have greatly attracted mankind for thousand years. But rigorous scientific approach has been conducted for only a few decades after molecular, cellular, genetic and genome approaches to understand life mechanisms become possible. In addition, proper introduction of model organisms and detailed experimental analysis greatly helped the establishment of basic concepts on longevity and lifespan of organisms. In addition, after the entry into 21st century, developed countries have increased senior populations over 65 yr old and the financial burden for medical care and welfare is increasingly felt. Hence human longevity and lifespan have become important research themes in many countries. Healthy longevity is now the keyword for human welfare. In this series of lectures, I plan to invite a few more experts on human gerontology. It is quite important for every person to know basics of human aging and how we adapt and/or confront it.
1. (Yanagida) Introduction on cellular life span and human longevity: How I was interested in cellular and organisms lifespan after years of chromosome research.
2. Professor Hiroshi Kondoh (Kyoto University, School of Medicine, Gerontology) Introduction of human longevity part 1.
3. (Yanagida) How I started to study human aging through blood metabolites
4. Professor Hiroshi Kondoh (Kyoto University, School of Medicine) Human longevity part 2.
Seminar for OIST researchers and students after lecture.
5. (Yanagida). Measuring biological aging
6. Professor Takehiko Kobayashi (Univ Tokyo), Seminar, afternoon for OIST students and researchers
7. (Yanagida) Cellular aging
8. (Yanagida) Genetics of aging
9. (Yanagida) Genetics of aging through the study of fission yeast G0 cells
10. (Yanagida) Human longevity and agin.
11. Professor Yoichi Nabeshima (Kyoto Univ) The role of Klotho for human longevity, Seminar, afternoon for OIST students and researchers
12. March 30 Invited speaker (not decided)
13. Professor Eisuke Nishida (Kyoto Univ, School of Biostudy) Lifespan of model organisms, Seminar, afternoon for OIST students and researchers
14. (reserved) a possible topic: Age-related human diseases
A312 Sensory Systems
The course will cover general concepts and specific modalities as detailed in the table below. Classes alternate between a lecture-style teaching and a journal club. Each lecture will be based on a textbook chapter (Kandel et al’s Principles of Neural Sciences, in combination with other, specialised books described in the “Textbooks” section) to cover basic and broad topics, but will also serve as an opportunity to introduce concepts required to understand the research article associated with the lecture.
Course Content:
1 (wk1) Overview lecture/intro Motivation; Modality, basic organisation: transduction, pathways, maps, integration, perception
2 (wk1) Sensory coding lecture/intro Relationship between a physical stimulus and sensation; intensity, threshold, adaptation, effect of background, discriminability
3 (wk2) Somatosensory system I lecture/intro
4(wk2) Somatosensory system I Journal club "Robust temporal coding in the trigeminal system" by Jones, Depireuz, Simons & Keller 2004
5(wk3) Somatosensory system II lecture/intro
6(wk3) Somatosensory system II Journal club "Active spatial perception in the vibrissa scanning sensorimotor system" by Mehta, Whitmer, Figueroa, Williams & Kleinfeld 2007
7(wk4) Hearing I lecture/intro
8(wk4) Hearing I Journal club "Ca2+ current-driven nonlinear amplification by the mammalian cochlea in vitro" by Chan & Hudspeth 2005
9(wk5) Hearing II lecture/intro
10(wk5) Hearing II Journal club "In vivo coincidence detection in mammalian sound localization generates phase delays" by Franken, Roberts, Wei, Golding & Joris 2015
11(wk6) Vision I lecture/intro
12(wk6) Vision I Journal club "Wiring specificity in the direction-selectivity circuit of the retina" by Briggman, Helmstaedter & Denk, 2011
13(wk7) Vision II lecture/intro
14(wk7) Vision II Journal club "Functional specificity of local synaptic connections in neocortical networks" by Ko, Hofer, Pichler, Buchanan Sjostrom & Mrsic-Flogel, 2011
15(wk8) Vision III lecture/intro
16(wk8) Vision III Journal club "Explicit information for category-orthogonal object properties increases along the ventral stream" by Hong, Yamins, Majaj & DiCarlo 2016
17(wk9) Chemical Senses I lecture/intro olfaction
18(wk9) Chemical Senses I Journal club "Random convergence of olfactory inputs in the Drosophila mushroom body" by Caron, Ruta, Abbott & Axel, 2013
19(wk10) Chemical Senses II lecture/intro gustation
20(wk10) Chemical Senses II Journal club "A chemosensory gene family encoding candidate gustatory and olfactory receptors in Drosophila", by Scott, Brady, Cravchik, Morozov, Rzhetsky, Zucker and Axel, 2001.
Assessment: Careful reading of the research article set for each journal club; Each student is asked to write a 1-page summary of the paper in their own words (Homework: 70%). The summary should include the context/rationale for the experiments, methods, results and the significance of the work. The summary will be assessed on clarity, balance, and whether or not student has understood the work. Class participation, 30%.
The course is aimed at students with a background in neuroscience (either at the BSc/MSc level or having successfully completed some of the basic neuroscience course offered at OIST). It assumes knowledge in cellular neurophysiology and neuroanatomy. Most relevant courses at OIST will include: B05 (Neurobiology; requirement), A405 (Emerging technologies in life sciences; desirable), B09 (Learning and behaviour; desirable), A310 (Computational neuroscience; highly desirable). B05 is the most important (in terms of subject matters listed on the course’s website), so a pass in this course will be a pre-requisite.
A401 Controversies in Science
The course Controversies in Science aims to develop critical thinking and argument, essential skills for effective independent scientists. The course will be flexible in content and presentation. Invited lecturers will present topics of some controversy or recent interest in science and lead debates by the students. We will also look at some historical controversies in different fields such as neuroscience and genetics, in which we will assign students to take sides by reading only one side of a specific argument, and encourage them to discuss the issue and arrive at a resolution in class.
- The Scientific Method, Ockham's Razor, Basic Philosophy of Science
- Boundaries of Science, L’Affaire Sokal, “Crackpots”
- Science & Racism in 1940s Germany and Japan
- Science and Capitalism: the pharmaceutical industry & biomedical science
- Science and Communism: Lysenko
- Scientific Misconduct I: Piltdown Man
- Scientific Misconduct II: Recent Cases
- Insights ahead of their time: Mendel and others
- Paradigm shifts: the reception of evolutionary biology
- Science and Religion: opposition to evolution
- Science and the media: the case of the autism-vaccination link, and others
- Science and the law: the suppression of psychedelics research
- Science and war: the making of the nuclear bomb
- The animal rights movement and science
- Conclusions: science as a social enterprise
A404 Measurement
Measurement is fundamental to scientists in all disciplines. This course will look at ways to make measurements and to avoid many of the pitfalls encountered in common and unusual measurements. A sound theoretical basis will be provided to allow students to go on to make their own choices with confidence and experience. Topics will include instrumentation, physical noise processes, signal transduction, models of small signal amplification, as well as modulation, detection, synchronous and lock-in detection, signal sampling techniques, digitization, signal transforms, Fourier analysis. Theoretical techniques to be presented will be centered around probability, probability theory, probability distributions, statistical inference, information theory, exact cases, and Gaussians.
- Information theory: signals, background and noise.
- Probability, distributions, Gaussians, Boltzmanns
- Sample size and Power of analysis
- Signal sampling techniques
- Frequency and digitization
- Fourier and other transforms
- Instrumentation
- Amplifiers
- Modulation
- Time-locked measurements, synchronous and asynchronous events
- Analog instruments
- Noise reduction
- Small signals
- Projects
- Projects
A405 Emerging Technologies in Life Sciences
This course is intended to provide an introduction to cutting-edge techniques that might be useful for research projects by graduate students at OIST. Such techniques include nucleotide sequencing, microarray, confocal laser scanning microscopy, microfluidics and neuroimaging. Each session will be composed of a lecture relevant to the technique. Where possible, hands-on training or research laboratory visits will also be provided, and technical presentations will be invited from leading experts. This course is intended to provide an introduction to cutting-edge techniques that might be useful for research projects by graduate students at OIST. Such techniques include nucleotide sequencing, microarray, confocal laser scanning microscopy, microfluidics and neuroimaging. Each session will be composed of a lecture relevant to the technique. Where possible, hands-on training or research laboratory visits will also be provided, and technical presentations will be invited from leading experts.
- Course Introduction & Nucleotide sequencing I (Background, Basics, PCR & qPCR, etc)
- Nucleotide sequencing II (Next generation, Genome analysis, etc)
- Nucleotide sequencing III (RNA sequencing, ChIP, Applications, etc)
- Microarray I (Background, Basics, DNA chips, etc)
- Microarray II (Protein chips, Applications, Future development, etc)
- Confocal laser scanning microscopy I (Basics, Live cell imaging, probes, etc)
- Confocal laser scanning microscopy II (Multi-color imaging, Multi-photon, etc)
- Confocal laser scanning microscopy III (Spectral imaging, FRAP, FRET, etc)
- Confocal laser scanning microscopy IV (PALM, SHIM, STED, etc)
- Microfluidics I (Background, Basics, Microfabrication, etc)
- Microfluidics II (Applications, Devices, Future development, etc)
- Single molecule imaging I (FCS, FCCS, etc)
- Single molecule imaging II (TIRF、FLIM, etc)
- Neuroimaging I (Optical, PET/CT, etc)
- Neuroimaging II (MRI/fMRI, SPECT, etc)
A409 Electron Microscopy
The course is designed as a mix of introductions into selected topics in the theory of transmission electron microscopy followed by practical demonstrations and hands-on exercises, which provide an opportunity to comprehend the concepts by experimenting with commonly-used image processing software. Students will be required to read and digest scientific papers for a subset of lecture topics on their own, which will subsequently be discussed jointly during student presentations with the goal to immerse them into the subject without passive consumption. The lectures cover several important concepts of the physics of image formation and analysis, which require a basic level of mathematics. An emphasis will be given to highlighting common properties between diffraction and image data and how to take advantage of tools from both techniques during the final image processing projects.
- History of the TEM / Design of a TEM - Lecture
- Design of a TEM (cont’d) - Lecture
- Design of a TEM (cont’d) - Lecture
- Demonstration of a TEM - Demo
- Math refresher / Electron waves - Lecture
- Fourier transforms - Lecture
- Intro to image processing software in SBGRID - Practical
- Image alignment - Practical
- Contrast formation and transfer - Lecture
- Image recording and sampling - Student presentation
- Applications in biology - Lecture
- Preparation of biological samples - Demo
- Low-dose cryo-EM - Student presentation
- 2D crystallography - Student presentation
- Overview of the single particle technique - Lecture
- Review of theory - Lecture
- Electron tomography (guest lecture) - Lecture
- Physical limits to cryo-EM - Student presentation
- Particle picking - Practical
- Classification techniques - Student presentation
- 3D reconstruction - Student presentation
- Image processing project 1 - Practical
- Resolution-limiting factors - Student presentation
- Refinement and sources of artifacts - Student presentation
- Image processing project 2 - Practical
- A sampling of original literature - Discussion
Ideally combined with A403 Strucutral Biology: Protein Xray Crystallography (Samatey) and A410 Molecular Electron Tomography (Skoglund)
A410 Molecular Electron Tomography
The course will show through theoretical and practical work how the 3D structure of a protein can be determined to about 2nm resolution directly in a buffer solution or in tissue. The students will get a direct hands-on experience of the processes involved in the practical and theoretical aspects of molecular electron tomography (MET). The students will be aware of how to carry out their own MET reconstruction and understand the limitations of the method and how to optimize its use.
- Learning the computer
- Learning the computer
- Practical Aspect of sample preparation for cryo-TEM
- Sample preparation for cryo-TEM
- Sample preparation for cryo-TEM; data collection
- 3D reconstruction
- 3D reconstruction
- 3D reconstruction
- Generating simulation-data
- 3D reconstruction from simulation-data
- 3D reconstruction from simulation-data
- Electron Microscopy: Sample Preparation
B05 Neurobiology
Description:
In this course students learn about the cellular and molecular basis of neuronal functions, and how individual electrical signals are integrated into physiological functions. The course is a combination of student-led presentations on each of the key topics, and also student presentations of several classic papers, and a series of laboratory explorations of the topics covered in class.
Aim:
This course provides an overview of cellular neurophysiology and looks closely at the fundamental aspects of action potentials and synaptic signalling, in preparation for other advanced courses in neuroscience.
Course Content:
Theory Classes
Membrane potential (I)
Methods for recording electrical signals
Cell membrane compositions
Intracellular and extracellular ionic compositions
Membrane potential, polarization, depolarization, hyperpolarization
Membrane capacitance
Electrical properties of cell membrane
Nernst equation
Calculation: Equilibrium potentials of Na+ and K+, based on extracellular and intracellular ionic compositions.
Membrane potential (II)
Selective permeability of Na and K ions
Resting membrane potential described by Goldman-Hodgkin-Katz equation
Hodgkin-Huxley membrane model circuit
Active transport
Na-K ATPase
Action potential (I)
Voltage-clamp recording; principle and practice
Cable properties of axonal membrane
Molecular structure of voltage-gated Na channels
Relationship between single Na channel currents vs whole cell Na currents
Channel activation, channel deactivation vs channel inactivation
Na current-voltage relationship
Voltage dependence of Na channel conductance
Mechanism of channel inactivation: the ball-and-chain model
Action potential (II)
Voltage-gated K channels: molecular structure
Single K channel vs whole cell K currents
K current-voltage relationship
Voltage dependence of K channel conductance
Mechanism of action potential generation and repolarization
Refractory period
Calculation: Amount of Na influx in response to a single action potential, and its impact on intracellular Na concentration (assuming cell size).
Synaptic transmission (I)
Structural organization of synapses
Equilibrium potential for Ca ion.
Voltage-gated Ca channels: molecular structure and subtype classification
Ca current-voltage relationship and conductance
Non-linear relationship between Ca and transmitter release.
Synaptic transmission (II)
Roles of Ca channels and K channels in transmitter release
Quantal nature of transmitter release; from binomial to Poisson theorem
Synaptic transmission (III)
Exocytosis, endocytosis, vesicle recycling
Molecular mechanisms of transmitter release
Ca domain in the nerve terminal: how to estimate its size?
Synaptic vesicle recycling and reuse
Vesicular transmitter refilling mechanism
Synaptic transmission (IV)
Ligand-gated ion channels: molecular structure
Nicotinic acetylcholine receptor, AMPA receptor, NMDA receptor,
Glycine receptor, GABA(A) receptor
EPSP/EPSC, IPSP/IPSC; Equilibrium potentials: calculation
Regulatory mechanisms for intracellular Cl concentration
Sensory transduction mechanisms
G protein-coupled receptors
Second messengers and targets
Muscle spindle, stretch-activated channels
Auditory transduction, from sound to action potentials
Visual transduction, from light to action potentials
Olfactory transduction, from odor to action potentials
Synaptic integration & modulation
Patellar-tendon reflex
Reciprocal inhibition
Postsynaptic inhibition, presynaptic inhibition
Feedback and feedforward inhibition
Lateral inhibition
Retrograde inhibition
Autoreceptor
Short-term facilitation and depression
Long-term potentiation (LTP) and depression (LTD)
Long-lasting LTP (LLTP)
Role of NMDAR in LTP
Role of glia in LTP
Laboratory Sessions (Takahashi Unit)
Membrane Potential
Action Potential
Synaptic Transmission
Synaptic integration & modulation
Course Type: Elective
Credits: 2
Assessment:
Student presentations on classic papers, class discussion, and a final report summarising what the student learned in the course.
Text Book:
Neuroscience, 5 edn, by Dale Purves, George J. Augustine, David Fitzpatrick, William C. Hall, Anthony-Samuel LaMantia, and Leonard E. White (2012) Sinauer
Ion Channels of Excitable Membranes, 3 edn, Bertil Hille (2001) Sinauer
Principles of Neural Science, 5 edn, Kandel, Schwartz, Messel, Siegelbaum and Hudspeth (2012) McGraw-Hill
Reference Book:
Fundamental Neuroscience 3 edn, Larry Squire, (2008) Elsevier (Academic Press)
The Synaptic Organization of the Brain, 5 edn, Gordon M. Shepherd (2003) OUP
Encyclopaedia of Neuroscience (5 volumes) (2009) Springer
From Neuron to Brain (Nicholls et al eds), Sinauer
B07 Statistical Methods
This course introduces basic principles and practical methods in statistical testing, inference, validation, and experimental design. The lectures cover the following topics: What is probability: frequentist and Bayesian views; probability distributions; Statistical measures; Statistical dependence and independence; Stochastic processes; Information theory; Statistical testing; Statistical inference: maximum likelihood estimate and Bayesian inference; Model validation and selection; Experimental design. Emphasis is put on the assumptions behind standard statistical methods and the mathematical basis for finding the right one.
- Introduction: Probability and Statistics
- Probability distributions, Expectation, Variance
- Joint and conditional distribution, Statistical independence, Correlation
- Confidence intervals
- P Values, t Test
- Multiple testing, ANOVA
- Nonparametric methods
- Linear regression, Maximum likelihood
- Multiple regression, Logistic regression, ROC
- Regularization, Bayesian methods
- PCA, ICA, Entropy, Mutual information
- Clustering, Mixture models
B08 Physics for Life Sciences
Course Coordinator: Bernd Kuhn
Principles of physics of central relevance to modern biological analysis and instrumentation are introduced with an emphasis on application in practical research areas such as electrophysiology, optogenetics, electromagnetics, the interaction of light and matter, and brain recording, stimulation, and imaging.
- Introduction - Physics in Biology: How physics contributes to life sciences.
- Nature of light
- Nature of matter
- Fundamentals on light and matter interaction
- Fluorescence and its applications
- Biophotonics
- Photosynthesis
- The physics of optogenetics
- Linear optics
- Microscopy
- Non-linear optics, lasers, two-photon microscopy, super resolution microscopy
- The physics of electron microscopy
- The physics of DNA, lipid membranes, and proteins
- Bioelectricity
- Electronics for electrophysiology
- Magnetic resonance
B09 Learning and Behavior
Course Coordinator: Gail Tripp
This course aims to introduce the function of the brain at the macroscopic level, namely, the control of behaviors and the cognitive and adaptive mechanisms behind it. The topics include the following: Reflex, classical and operant conditioning. Perception, adaptation, and attention. Feedback and predictive control. Procedural and declarative memory. Motivation and emotion. Thinking and reasoning. Communication and language. Psychological disorders. Clinical and experimental neuropsychology.
Research methods (I)
- Ethics
- Hypothesis testing
- Dependent and independent variables
- Reliability and validity
- Bias, blinding
Research methods (II)
- Data collection methods
- Observation
- Surveys
- Experimental and quasi experimental designs
- Data analysis
Learning and behavior (I)
- Classical, Pavlovian, respondent conditioning (elicited responses)
- Operant, instrumental conditioning (instrumental responses)
Learning and behavior (II)
- Reinforcement and punishment
- Operant schedules
Learning and behavior (III)
- Behavior modification
- Applications
Motivation and reward
- Drug addiction
- ADHD
Memory and cognition (I)
Memory and cognition (II)
Perception and attention
Behavioral neuroscience (I)
Behavioral neuroscience (II)
Genes and behaviour
Animal models
Life span
B10 Analytical Mechanics
Course Coordinator: Mahesh Bandi
Mastery of the concepts and techniques of analytical mechanics is essential to a deep understanding of physics. This course begins with basic principles and proceeds to the Newtonian equations of motion and laws of conservation. We use the Lagrange formalism to describe particle motion in multiple modes, before covering the equations of Euler and Hamilton, and canonical transformations. The calculus of variation is used to develop Maupertuis’s principle and the Hamilton-Jacobi equations, providing a starting point for the consideration of waves in later courses. This course is taught from the unifying principles of symmetry and least action.
- The Principle of Least Action
- Equations of Motion: Galileo and Lagrange
- Equations of Motion: Newton
- Conservation Laws: Energy, Momentum, and Angular Momentum
- Integration of Equations of Motion
- Breakup, Collision, and Scattering of Particles
- Harmonic Oscillations: Free, Forced, and Damped Oscillations, Resonance
- Rigid Body Dynamics: Angular Velocity, Inertia Tensor, Angular Momentum
- Equations of Motion for Rigid Body
- Euler's Equations
- Dynamics of Rigid Bodies in Contact
- Hamilton's Equations
- Maupertuis' Principle
- Canonical Transformations and Liouville's Theorem
- Hamilton-Jacobi Equations
B11 Classical Electrodynamics
Course Coordinator: Tsumoru Shintake
A graduate course in analytical mechanics, covering the essential equations and their applications, to prepare for later courses in electrodynamics and quantum physics. This course assumes undergraduate level knowledge of mechanics and a firm grasp of calculus and vector mathematics. An understanding of static electromagnetic fields is extended through Maxwell’s equations to a discussion of dynamic vector fields and electromagnetic waves. Along the way, numerous physical and technical applications of these equations are used to illustrate the concepts, including dielectrics and conductors, wave guides, and microwave engineering. Special relativity is introduced with discussion of relativistic and non-relativistic motion and radiation, using linear accelerators and synchrotron radiation as illustrative applications.
- Charge and Gauss's Law
- Current and Ampere's Law
- Divergence and Rotation
- Induction
- Capacitance and Inductance
- Maxwell's Equation 1
- Maxwell's Equation 2
- Vector and Scalar Potentials
- Electromagnetic Waves
- Energy, Dispersion
- Impedance Concept
- Reflection and Matching Condition
- Relativistic Equation of Motion
- Radiation from a Moving Charge
- Synchrotron Radiation
B12 Statistical Physics
Course Coordinator: Nic Shannon
Matter can exist in many different phases. The aim of this course is to explain why, and how one phase can transform into another. Starting from the question “what is temperature?”, the ideas of entropy, free energy, and thermal equilibrium are introduced, first in the context of thermodynamics, and then as natural consequences of a statistical description of matter. From this starting point, a simple physical picture of phase transitions is developed, with emphasis on the unifying concept of broken symmetry. The course is designed to be accessible to students from a wide range of educational backgrounds. It will be assessed through weekly problem sets, and a final presentation on a modern example of the application of statistical physics ideas, chosen by the student.
- General overview of phase transitions - what are they, and where do they happen?
- Introduction to the basic concepts of thermodynamics - temperature, entropy, thermodynamic variables and free energy - through the example of an ideal gas.
- Introduction to the basic concepts and techniques of statistical mechanics - phase space, partition functions and free energies. How can we calculate the properties of an ideal gas from a statistical description of atoms?
- Introduction to the idea of a phase transition. How does an non-ideal gas transform into a liquid?
- The idea of an order parameter, distinction between continuous and first order phase transitions and critical end points. How do we determine whether a phase transition has taken place?
- Magnetism as a paradigm for phase transitions in the solid state - the idea of a broken symmetry and the Landau theory of the Ising model.
- Universality - why do phase transitions in fluids mimic those in magnets? An exploration of phase transitions in other universality classes, including superconductors and liquid crystals.
- Alternative approaches to understanding phase transitions: Monte Carlo simulation and exact solutions.
- How does one phase transform into another? Critical opalescence and critical fluctuations. The idea of a correlation function.
- The modern theory of phase transitions - scaling and renormalization.
- 11.To be developed through student presentations: modern applications of statistical mechanics, with examples taken from life-sciences, sociology, and stock markets.
B13 Theoretical and Applied Fluid Mechanics
We will introduce basic concepts of flow of fluids. We will discuss conservation laws and constitutive equations. We will derive the Navier-Stokes equations, and study its exact and approximate solutions. Last, we will introduce the theory of hydrodynamic stability and then discuss turbulent flows. Throughout the course we will discuss a wide spectrum of flows from nature and engineering.
- Overview of fluid mechanics
- Kinematics of flow
- Review of Tensors and the Stress Tensor
- Conservation Laws: Mass, Momentum, and Energy
- Constitutive Equations: the Navier-Stokes Equations, Boundary Conditions.
- Potential Flows
- Vortex motion
- Dimensional analysis and similarity
- Exact solutions of viscous flows
- Creeping Flows
- Boundary Layers
- Hydrodynamic Stability
- Turbulent flows
B14 Theoretical and Applied Solid Mechanics
Course Coordinator: Gustavo Gioia
Students are introduced to the concepts of stress and strain, and discuss conservation laws and constitutive equations. We derive the Navier equations of linear elasticity, introduce the Airy stress-function method, and solve problems to illustrate the behavior of cracks, dislocations, and force-induced singularities in applications relating to materials science, structural engineering, geophysics and other disciplines.
(1) Mathematical Preliminaries:
- Summation convention, Cartesian, spherical, and cylindrical coordinates.
- Vectors, tensors, linear operators, functionals.
- Eigenvalues and eigenvectors of second-order symmetric tensors, eigenvalues as extrema of the quadratic form.
- Fields, vector and tensor calculus.
(2) Stress, Strain, Energy, and Constitutive Relations:
- Cauchy stress tensor, traction, small strain tensor, compatibility.
- Strain energy, strain energy function, symmetries, elastic modulii.
(3) Elasticity and the Mechanics of Plastic Deformation:
- Navier equations, problems with spherical symmetry and problems with cylindrical symmetry (tunnels, cavities, centers of dilatation).
- Anti-plane shear. Plane stress, plane strain.
- The Airy stress-function method in polar and Cartesian coordinates.
- Superposition and Green's functions.
- Problems without a characteristic lengthscale.
- Flamant's problem, Cerruti's problem, Hertz's problem.
- Load-induced versus geometry-induced singularities (unbounded versus bounded energies).
- Problems with an axis of symmetry.
- Disclinations, dislocations, Burgers vector, energetics; relation to plastic deformation in crystalline solids.
(4) Fracture Mechanics:
- The Williams expansion, crack-tip fields and opening displacements via the Airy stress-function method (modes I, II) and via the Navier equations (mode III), crack-tip-field exponents as eigenvalues, stress intensity factors.
- Energy principles in fracture mechanics, load control and displacement control.
- Energy release rate and its relation to the stress intensity factors, specific fracture energy, size effect, stability. The Griffith crack and the Zener-Stroh crack. Anticracks.
(5) Possible Additional Topics (if time allows):
- Elasticity and variational calculus, nonconvex potentials, two-phase strain fields, frustration, microstructures.
- Stress waves in solids, P, S, and R waves, waveguides, dispersion relations, geophysical applications.
- Dislocation-based fracture mechanics, the Bilby-Cotterell-Swindon solution, small- and large-scale yielding, T-stress effects, crack-tip dislocation emission, the elastic enclave model.
- Deterministic versus statistical size effects in quasibrittle materials.
- Vlasov beam theory, coupled bending-torsional instabilities.
- Dynamic forms of instability, nonconservative forces, fluttering (Hopf bifurcation).
B15 Immunology
In this course, students will learn basic principles of immunology including the cellular and molecular mechanism of innate and adaptive immunity. The course also provides the clinical importance of immunology in various diseases such as HIV/AIDS, autoimmunity and allergy. Then, students will learn how the immune response can be manipulated by vaccination to combat infectious diseases and cancer.
- Basic concepts in immunology
- Innate immunity
- Antigen recognition by B-cell and T-cell receptors
- The generation of lymphocyte antigen receptors
- Antigen presentation to T lymphocytes
- Signaling through immune system receptors
- The development and survival of lymphocytes
- T cell-mediated immunity
- The humoral immune response
- Dynamics of adaptive immunity
- The mucosal immune system
- Failures of host defense mechanism
- Allergy and Hypersensitivity
- Autoimmunity and Transplantation
- Manipulation of the immune response
B16 Ecology and Evolution
Course Coordinator: Evan Economo
This course covers biological phenomena at or above the scale of a single organism. We will broadly cover topics in evolutionary biology and ecology including but not limited to population genetics, animal behavior, adaptation and natural selection, speciation, phylogenetics, population biology, community ecology, ecosystem ecology, and macroecology.
Course Content:
- Introduction, levels of organization in biological systems.
- Taxonomy, systematics, phylogenetics.
- Biodiversity
- Energy flows and transformations in biological systems.
- Genomics and Genetics of Adaptation
- Physiological ecology.
- Population dynamics and regulation
- Life histories
- The evolution of sex and the evolution of cooperation
- Community Ecology
- Ecosystem Ecology
- Global Climate system and Climate change
- Conservation Biology
B20 Introductory Evolutionary Developmental Biology
This course will provide an introduction to Evolutionary Biology focusing on the developmental process of multicellular organisms for students with and without an undergraduate background in this field. Two major goals in this course will be to understand evolutionary changes in development and to learn modern creatures and technologies employed for addressing issues in evolutionary developmental biology.This course presents the basic principles and recent findings in evolutionary developmental biology.
- Animal phylogeny
- Gain and loss in evolution
- Gene homology
- Cell homology
- Gene expression
- Basic body plan I: Embryogenesis
- Basic body plan II: Main body axes
- Basic body plan III: Main body axes
- Signaling pathways and gene regulatory networks
- Body axes in basal metazoans
- Multicellularity
- Research tools I: Genome/transcriptome analysis and molecular phylogeny
- Research tools II: New animal models
- Research tools III: Gene function analysis
No prior knowledge assumed
B21 Biophysics of Cellular Membranes
Description: Students will learn several basic concepts of biophysics including thermal conformational fluctuation and thermal diffusion, and how cells might take advantage of these physical processes to enable their functions. As a biological paradigm, the cellular membrane system (and their functions), with a special attention paid to signal transduction in the plasma membrane, will be extensively covered. This is because the membranes are critically important for a variety of cellular processes, in the fields of cancer biology, immunology, neuroscience etc., and also because the membrane system provides us with an interesting and useful biological paradigm to learn how the life processes are made possible by thermal-physical processes. As a way of directly “seeing” the thermal, stochastic processes exhibited by receptors and downstream signaling molecules undergoing signaling in live cells, the methods of single-molecule imaging-tracking and manipulation will be discussed quite extensively. Through this course, students will better understand the interdisciplinary field of biology, chemistry, physics, and mathematical science.
1. Introduction to Biophysics
2. Biological Membrane Structure and Molecular Dynamics
3. Signaling in the Plasma Membrane I
4. Single-molecule Imaging and Manipulation of Plasma Membrane Molecules
5. Interaction between the Plasma Membrane and the Cytoskeleton
6. Force Involved in Organizing Membrane Molecules
7. Domain Structures of the Plasma Membrane
8. Signaling in the Plasma Membrane Enabled by Its Meso-Scale Domain Organization
9. 3D-Organization of the Plasma Membrane: Endocytosis and Exocytosis
10. Membrane Deformation
11. Interaction between the Cytoplasmic Membranes and the Cytoskeleton
12. Tubulovesicular Network in Cells
13. Signaling in the Plasma Membrane II
14. Biological Meso-scale Mechanisms
B22 Computational Methods
The course starts with basic programming using Python, with some notes on other computing frameworks. Students then get acquainted with data manipulation and visualization using “numpy” and “matplotlib.” After learning how to define one’s own function, students learn iterative methods for solving algebraic equations and dynamic simulation of differential equations. The course also covers basic concepts in stochastic sampling, distributed computing, and software management. Toward the end of the course, each student will pick a problem of one’s interest and apply any of the methods covered in the course to get hands-on knowledge about how they work or do not work.
1. Introduction to Python
2. Vectors, matrices and other data types
3. Visualization
4. Functions and classes
5. Iterative computation
6. Ordinary differential equation
7. Partial differential equation
8. Optimization
9. Sampling methods
10. Distributed computing
11. Software management
12. Project presentation
For each week, there will be homework to get hands-on understanding of the methods presented.
B23 Molecular Evolution
Course Coordinator:
Description:
Life sciences have been greatly influenced by the progress of DNA sequencing technologies. The field of Evolutionary Biology is no exception, and increasingly relies upon fast generation of DNA sequences, that are analysed using fast evolving bioinformatics tools. The aim of this course is to introduce the basic concepts of molecular evolution to students of all scientific backgrounds. We will explore some important questions in Biology, and through concrete examples, determine how molecular evolution theory help answering them. The students will also learn how to use a number of widely used bioinformatics tools.
Aim:
Course Content:
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DNA, RNA and protein
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Replication and mutation
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Building a genome
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Gene
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Selection
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Drift and population genetics
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Evolution of species
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Using DNA to build phylogenies
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Putting dates on trees
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High throughput sequencing: the rise of genomics and transcriptomics
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Working with genome-scale data: Annotation, gene orthology, RNAseq…
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Genomics of symbiosis
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Amplicon metagenomics and environmental DNA
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Ancient DNA and protein
Course Type:
Credits:
Assessment:
Text Book:
Prior Knowledge:
Assumes general knowledge in biology; ideally follow-on course from B16 Ecology and Evolution
PD1 Professional Development I for 2017 Students
| Coordinator | Ulf Skoglund |
| Description |
This course aims to develop knowledge and skills important for leadership in scientific research and education. The three main components of the course are (1) weekly seminars covering basic principles of research conduct and ethics, scientific communication, and aspects of science in society, including a visiting speaker program (2) a cross-disciplinary group project, (3) practical experience to develop presentation and teaching skills.
Seminars Seminars are held every Friday afternoon throughout the year. It is imperative that you not only attend the seminars but that you also engage by participating in discussion and asking questions. Visiting speakers will be invited each month to give seminars and lead interactive discussions. Visiting speakers will include leaders from major corporations, research institutes and scientific laboratories and internationally leading researchers from different fields. This is an opportunity to learn what the leaders see as important during their successful careers, and also a chance to learn how to interact and present yourself in ways that may lead to valuable connections for your future.
Group Project. The group project component aims to develop skills required for effective teamwork, including leadership, project management, cooperation and creative interaction, cross-disciplinary communication, and coordination of group activity. Group project work is timetabled on Friday afternoons for two hours every second week, alternating with presentation and teaching skills training. Timing of project activity is flexible and different times may be decided by the group. The project component will require involvement in a student led group project. Projects will not be directly supervised by a faculty member, but there will be opportunities for consultation where certain expertise is required. The nature of possible projects will be explained in class but they may include development of new research tools and applications, inventions to solve problems, field studies, or creation of resources for research and learning. There will be a self-assessment requirement by group members to recognize the contributions of different members, and an overall grade based on a final presentation. A prize will be awarded for the best project. Scientific Communication Skills Being able to deliver a clear message about your research is a valuable skill. Competition for jobs both in and out of academia is fierce. Researchers, whether in academia or industry, need to develop their personal skill sets not only to do outstanding research, but also to write papers, teach and demonstrate the impact and relevance of their work. The scientific communication skills component of PD1 comprises a set of opportunities for students to improve academic presentation and scientific writing skills. |
| Aim | The aim of this course is to provide information essential to beginning one's career as a professional scientist, and to develop skills fundamental to modern scientific practice. |
| Mandatory | |||
| Credit | 1 | ||
| Assessment | Attendance and participation | ||
| Text Book | |||
| Reference Book | |||
Detailed Content
Term 1 Module: Research conduct and ethics
- laboratory procedures, conduct and safety
- record keeping and data management
- plagiarism
- research misconduct
- authorship
- peer review
- conflicts of interest
- research with animals
- research with human subjects
Other Courses Offered
Special Topics
Biological Networks: Bioinformatics and Modelling
Professor Igor Goryanin
Day 1 Introduction / Theory. Enzyme kinetics (Goryanin)/ Practicals.
Introduction, installing software (Goryanin)
Day 2 Theory: Metabolic Pathways. Graph analysis of Biological networks. Standards in Systems Biology(Goryanin)
Day 3 Theory: Flux Balance Analysis. Stoichiometric matrix and its properties. Extreme pathways (Goryanin)
Day 4 Theory: Applications in Systems Biology. (Goryanin). Practicals. Tests (Goryanin/Sorokin)
Two Lectures and four practicals from 25th of July till 18th of August.
Computational Biology: Artificial Intelligence for Bioinformatics
Professor Hiroaki Kitano (OIST adjunct professor)
with other presenters
7/22 (Mon) 09:00-13:00: Kitano & Asai (Intro /Hands-on I Physiological Modeling)
7/23 (Tue) 09:00-13:00: Kitano (Signal Transaction/Cell Cycle)
7/24 (Wed) 09:00-13:00: Funahashi (Hands-on Ⅱ CellDesigner Modeling)
7/25 (Thu) 09:00-13:00: Kitano (AI for Life Science/Wrap-up)
Geometry and Topology
Professor Anastasiia Tsvietkova
Select seminar topics in Geometry and in Topology, over two terms.
Holography and Anti de Sitter space
Professor Yasha Neiman
with Lecturer Linqing Chen
Skill Pills AY2017-2018
Skill Pill: Regular Expressions August 28 and 30, 1PM to 3PM
Skill Pill: Hands-on Electronics August 23, 27 and 29, from 1PM to 4 or 5PM
Skill Pill: Git July 10 and 12, 10AM - 12PM
Skill Pill: GIMP June 25 and 28, 1PM - 3PM
Skill Pill: BLAST July 17 and 18, 10AM - 12PM
Skill Pill: Building and Maintaining a CV July 3 and 5, 10AM - 12PM
Skill Pill: Terminal May 22, 24, 28, 10AM to 12PM
Skill Pill: Filmmaking for Scientists May 30, 31, June 6, AM
Skill Pill: 3D Printing May 14, 16, 10AM to 12PM
Skill Pill: Calculus of Variations April 23. 25, 27, 10AM to 12PM
Skill Pill: Teaching Techniques April 17, 19, 10AM to 12PM
Skill Pill: Phylogenetic Reconstruction April 10 (1PM to 3PM) and 12 (1PM to 4PM)
Skill Pill: Intro to Programming March 26, 29, April 2, 5, 1PM to 3PM
Skill Pill: Skill Pill: Android Development April 4, 1PM to 5PM
Skill Pill: LabVIEW March 20, 23, 27, 30, 10AM to 12PM
Skill Pill: Philosophy of Mind Feb 27, Mar 2, 6, 9, 10AM and 11AM to 12PM
Skill Pill: Bayesian statistics January 18, 19, 25 and 26, 10AM to 12PM
Skill Pill: Visualizing Tomography Data February 6, 8 and 13, 10AM to 12PM
Skill Pill+: Nanoparticles by Design December 9 (Saturday) 10AM to 6PM
Skill Pill: Super-resolution Microscopy December 6, 7 or 8, 10AM to 12PM
Skill Pill: Electronics for Computational Neuroscience November 18 and 25 (Saturdays)
Skill Pill: Planning Your Scientific Journey Every Wednesday from October 4th to November 1st, 12PM to 1PM
Skill Pill: LaTeX November 6, 7, 13 and 14, 1PM to 3PM
Skill Pill: GPU November 7, 9 and 14, 10AM to 12PM
Skill Pill: Digital Marketing Wednesday October 11, from 10AM to 12PM
Skill Pill: MATLAB October 3, 5, 10 and 12, 10AM~12PM
Skill Pill: Keynote September 27 and 28, 10AM~12PM
Skill Pill: Raspberry Pi Saturday September 9, 10AM to 6PM