G-RISE Trainee Program Overview
Once admitted to the program, G-RISE students are expected to complete specified coursework and training within the two first years of their Ph.D. career. The program activities are designed to prepare a diverse pool scientists earning a Ph.D. for competitive careers in the biomedical field by training students to identify and solve pressing biologicalproblems using quantitative interdisciplinary approaches
I-BioSTeP trainees will complete core courses within their own individual graduate groups, while doing research rotations in assigned faculty labs. In year 1, trainees will also take the semester-long 1- unit Responsible Conduct of Research Course (required across all participating graduate groups) and two semesters of their group’s 1-unit seminar series.
The trainees will focus exclusively on research with their chosen advisors and complete the three I-BioSTeP courses, two in the Fall semester and one in Spring, which will serve as electives in their respective primary graduate programs:
Imaging and Spectroscopy
This is a semester-long course, taken by trainees in Fall of Year 2, that will emphasize laboratory experience for students after assimilation of the theoretical basis of different imaging and spectroscopic techniques. It will start by introducing current biomedical problems and related research to students, who will need to envision ways to improve our understanding and/or to advance toward potential solutions.
Molecular and Cellular Biotechnology
This course will give students practical, hands-on experience in modern molecular and cell biological techniques. This semester-long course will cover three broad areas: 1) bacterial and cell culture, 2) protein production and engineering, and 3) molecular cloning and genetic engineering.
Computation and Modeling
This will include Atomistic Molecular Dynamics (Protein Structure), Coarse grained Molecular Dynamics (to model long-chain macromolecules, e.g. DNA or cell cytoskeletal proteins), Monte Carlo simulations including the Gillespie algorithm (to model chemical reactions in the cellular environment, as well as larger scale ecological processes such as bacterial colony formation and foraging ), mathematical modeling using PDEs (to model the mechanics of fluid flows and elastic deformations in cells and biomaterials) and ODEs to model systems-level networks such as in intercellular signaling) and also on statistical modeling, data and image analysis (important for all quantitative analysis of biological research including in cell and developmental biology).
NIH Grant Number: T32 GM141862
Please use this grant number in acknowledgements for posters and publications