Start Date: Summer
Length of Assignment: 3 months, 40/hrs per week, either remote or on site
Preferred Majors/Disciplines: biomedical, chemical, electrical, or mechanical, bioinformatics/computational biology, applied math, computer science or other pharmaceutical sciences
Education Level: M.S/Ph.D/Pharm.D degree in progress
Genentech is looking for a highly motivated graduate student who is interested in the cross-section of deep learning and mechanistic modeling to work as a summer intern with the Quantitative Systems Pharmacology (QSP) group within the Preclinical and Translational Pharmacokinetic/Pharmacodynamic (PKPD) department of Development Sciences.
This is an exciting opportunity to work with QSP scientists on a highly impactful project to predict the PK and PD relationship for novel drugs using Neural Ordinary Differential Equations (Neural ODE) and/or other deep learning methods. For this project, the intern will have the opportunity to work with various in-house QSP models and ML algorithms.
Responsibilities
During the project, the intern will become familiar with Genentech's workflow for model development and its contribution to drug development. The research project will be primarily implemented in Python and MATLAB and their associated toolboxes (PyTorch, SimBiology, Machine Learning and Parallel Computing toolboxes) and utilize Genentech's in-house HPC cluster. The summer intern is expected to give a formal presentation at the end of the program. Minimum duration of the internship is for 3 months, however start date and end date timing can be flexible.
Who you are
Early Development Science
Full time
Temporary (Fixed Term)
Jan 22nd 2022
202201-102632