Intern - Quantitative Systems Pharmacology, Machine Learning

internship - full time, unpaid

Genentech
South San Francisco, CA
Closed
Posted 48 Days ago
Genentech
South San Francisco, CA
internship - full time, unpaid
Posted 48 Days ago
Closed

Description

Intern - Quantitative Systems Pharmacology, Machine Learning South San Francisco California, United States of America Job ID:201902-106439 -The Position Title Integration of ML-based approaches into the technical workflow of QSP model development Description: Genentech is looking for a summer intern in the Quantitative Systems Pharmacology (QSP) group within the Pharmacokinetic/Pharmacodynamic Sciences Division of Development Sciences. The summer intern will work with scientists in the QSP group on a highly impactful project to evaluate the application of ML-based approaches in the workflow of QSP model development. The project includes implementation of various machine learning methods using the inputs (system parameters) and outputs (a set of specific simulated biomarkers) of QSP models. Once trained, the ML-based equivalent of a QSP model will be computationally more efficient than running an ODE-based QSP model. We will take a systematic approach to evaluate the application of the ML-based system to increase efficiency and robustness of various steps in the QSP workflow including reference patient calibration, virtual cohort generation, sensitivity analysis, and analyses of the model predictions. For this project, the intern will have the opportunity to work with in-house QSP models used to inform development of a range of drugs in our portfolio and become familiar with Genentechs workflow for QSP model development and its contribution to drug development. The research project will primarily be executed in R and MATLAB and associated toolboxes (SimBiology, Statistics, Machine Learning and Parallel Computing) and the Rosalind 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, the timing of the start date and end date can be flexible. Who you are: Youre someone who wants to influence your own development. Youre looking for the opportunity to pursue your interests and become proficient in a technique/skill that can influence/improve drug development -M.S/Ph.D/Pharm.D. degree in progress engineering (biomedical, chemical, electrical, and mechanical), applied math, computer science, pharmaceutical sciences, or systems biology related fields preferred -3+ years experience with Matlab and R programming -Hands-on experience with machine learning methods -Strong interpersonal and oral/written communication skills -Applicants must be currently enrolled in an academic program Contact: Iraj Hosseini Scientist, Translational & Systems Pharmacology PKPD Sciences Genentech, Inc. South San Francisco, CA hosseini@gene.com -Who We Are A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work. The next step is yours. To apply today, click on the "Apply online" button. Genentech is an equal opportunity employer & prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital & veteran status. For more information about equal employment opportunity, visit ourGenentech Careers page. -Job Facts -Job Function Internship -Location -South San Francisco California, United States of America -Company/Division Pharmaceuticals -Schedule Full time -Job type Temporary (Fixed Term)

Skills

matlab, statistics, machine learning, computer science, systems biology, genetic analysis, r programming, parallel computing, research, microsoft excel, math, engineering, cancer, applied mathematics, biomarkers

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