PhD Intern: QSP Modeling for CVRM PK/PD with AI

Genentech; South San Francisco (CA); On-site; USD 59,000 - 84,000; Full time

Benefits offered by this job

Paid internship

On-site in South San Francisco

Job summary

Genentech, Inc. in South San Francisco is offering a 12-week, full-time internship in Translational PKPD and QSP Modeling for CVRM diseases. The role focuses on mechanistic QSP modeling in MATLAB/SimBiology, with emphasis on linking drug pharmacology to physiological outcomes.

The internship requires active PhD enrollment and expertise in MATLAB, R, or Python, plus data fitting and model calibration skills. On-site work, with a competitive stipend and paid holidays.

Qualifications

• Must be pursuing a PhD (enrolled student).
• Majors include Bioengineering, Biomedical Engineering, Chemical Engineering, Pharmaceutics/Pharmacometrics, Applied Mathematics, Computational/Systems Biology, AI & machine learning.

Responsibilities

• Develop, extend, or integrate mechanistic QSP models of CVRM physiology and disease in MATLAB/SimBiology.
• Represent drug pharmacology and its links to physiological outcomes in these models.
• Calibrate and validate models against published preclinical and clinical data.
• Use simulation, sensitivity analysis and virtual populations to address questions from drug teams.
• Leverage AI coding tools to accelerate model development with verified results.
• Present results to project teams and the intern poster session, and in a written report.

Education

PhD student (enrolled)

Tools

MATLAB (SimBiology)

R

Python

Job description

Genentech, Inc. in South San Francisco is offering a 12-week, full-time internship in Translational PKPD and QSP Modeling for CVRM diseases. The role focuses on mechanistic QSP modeling in MATLAB/SimBiology, with emphasis on linking drug pharmacology to physiological outcomes.

The internship requires active PhD enrollment and expertise in MATLAB, R, or Python, plus data fitting and model calibration skills. On-site work, with a competitive stipend and paid holidays.