Soft Materials Graduate Program

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The Brandeis Soft Materials Graduate Program is an immersive training program that prepares the next generation of material researchers to advance interdisciplinary materials research and technology to improve the quality of life. The training provides the necessary background to investigate emergent phenomena in soft materials such as colloids, polymers and liquid crystals. For students interested in Soft Materials research, the SM Program can provide specialization that supplements graduate study in Physics.

Those who choose the SM track will receive a Ph.D. degree in Physics with an additional specialization in Soft Materials and then pursue research in the Materials Research Science and Engineering Center (MRSEC).

Admission to the Soft Materials Program

Students interested in the Soft Materials specialization will meet with the SM Physics liaison to discuss requirements and program of study, and will be invited to apply for admission to the Soft Materials Program. Admission of each student to the Soft Materials specialization will require the approval of the student’s Ph.D. program, the Ph.D. program’s liaison to the SM program, and the SM director. Ordinarily, students will be admitted to the program at the beginning of or during their first year, but later admissions will be allowed if the student is able to satisfy the program requirements.

Curriculum

To earn the SM specialization, students must complete three of the four courses designated as core courses of the SM program, one of the two laboratory courses designated as a laboratory course in the SM program and one elective course. These courses introduce students to soft materials, statistical mechanics, experimental techniques and biophysics.

Courses for Soft Materials and Core Courses for Soft Materials Program:

PHYS 105a Biological Physics
Physical forces in living matter are studied from the perspective offered by statistical mechanics, elasticity theory, and fluid dynamics. Quantitative models for biological structure and function are developed and used to discuss recent experiments in single-molecule biology. Usually offered every second year.

PHYS 163a Statistical Physics and Thermodynamics
The thermal properties of matter. Derivation of thermodynamics from statistical physics. Statistical theory of fluctuations. Usually offered every year.

PHYS 163b Principles of Soft Materials
Introduction to non-equilibrium statistical mechanics and applications of equilibrium and non-equilibrium statistical mechanics to understanding emergent phenomena in soft materials such as colloids, polymers and liquid crystals. Usually offered every other year.

1 of the following 2 lab courses:

QBIO 120b Quantitative Biology Instrumentation Laboratory
Focuses on optical and other instruments commonly used in biomedical laboratories to make quantitative measurements in vivo and in vitro. Students disassemble and reconfigure modular instruments in laboratory exercises that critically evaluate instrument reliability and usability and investigate the origins of noise and systematic error in measurements. Usually offered every year.

PHYS 169b Advanced Laboratory
Experiments in a range of topics in physics, possibly including selections from the following: wave optics, light scattering, Nuclear Magnetic Resonance, numerical simulation and modeling, phase transitions, laser tweezers, chaotic dynamics, and optical microscopy. Students work in depth on three or four experiments during the term. This course is co-taught with PHYS 39a. Usually offered every year.

Elective Courses for Soft Materials Program:

PHYS 104a Condensed Matter Physics
Mechanical, thermal, and electronic properties of matter including fluids, solids, liquid crystals, and polymers. Simple models of matter are developed and used to discuss recent experimental findings. Usually offered every second year.

QBIO 110a Numerical Modeling of Biological Systems
Prerequisite: MATH 10a and b or equivalent.
Modern scientific computation applied to problems in molecular and cell biology. Covers techniques such as numerical integration of differential equations, molecular dynamics and Monte Carlo simulations. Applications range from enzymes and molecular motors to cells. Usually offered every second year.

COSI 178a Computational Molecular Biology
Open to advanced undergraduate students and graduate students.
Information and computing technologies are becoming indispensable to modern biological research due to significant advances of high-throughput experimental technologies in recent years. This course presents an overview of the systemic development and application of computing systems and computational algorithms/techniques to the analysis of biological data, such as sequences, gene expression, protein expression, and biological networks. Hands-on training will be provided. Usually offered every other year.
Mr. Hong

NBIO 136b Computational Neuroscience
Prerequisite: MATH 10a and either NBIO 140b or PHYS 10a or approved equivalents.
An introduction to concepts and methods in computer modeling of neural systems. Topics include single and multicompartmental models of neurons, information representation and processing by populations of neurons, synaptic plasticity and models of learning, working memory, decision making and neural oscillations. Introductory tutorials in computer coding in Matlab will be featured throughout the course. Usually offered every second year.
Mr. Miller

BCHM 102a Quantitative Approaches to Biochemical Systems
Prerequisite: BCHM 100a or equivalent.
Introduces quantitative approaches to analyzing macromolecular structure and function. Emphasizes the use of basic thermodynamics and single-molecule and ensemble kinetics to elucidate biochemical reaction mechanisms. Also discusses the physical bases of spectroscopic and diffraction methods commonly used in the study of proteins and nucleic acids. Usually offered every year

NPHY 115a Dynamical Systems
Prerequisites: MATH 10b and MATH 15a or PHYS 20a or equivalent.
Covers analytic, computational and graphical methods for solving systems of coupled nonlinear ordinary differential equations. We study bifurcations, limit cycles, coupled oscillators and noise, with examples from physics, chemistry, population biology and many models of neurons. Usually offered every third year.