Postdoctoral Fellow- Machine Learning Drug Discovery, Watkins Lab (roche)

Job Description

The Watkins lab within Genentech Computational Sciences, Machine Learning Drug Discovery pillar seeks exceptional postdoctoral fellows with a demonstrated research background in structural biology, computational protein design, or machine learning, a passion for independent research and technical problem-solving, and a proven ability to develop and implement ideas from research. The successful postdoc will study the thermodynamic, chemical, and statistical stability of therapeutic proteins and uncover new, highly interpretable models that describe how these stability traits do and do not correlate. 

Our mission is to develop and apply cutting-edge methods in designing novel molecules. Researchers will primarily focus on computational protein design and the application of deep generative models but should be broadly interested in physics-, chemistry-, and biology-informed methods at the interface of wet lab biology and computational modeling that can help drive and sharpen the research questions we study. Fundamentally, our research goals allow us to collaborate closely with and–contribute uniquely to–many different project teams across the organization.

Key Responsibilities

• Participate in cutting-edge research in physics-based modeling and machine learning towards applications to drug discovery, design, and development.

• You will collaborate closely with cross-functional teams across gRED to solve complex problems in the life sciences e.g., structural and computational biology, computational chemistry, antibody engineering, etc..

Qualifications

• Completed PhD with at least one first-author paper

• At least three years of relevant work/research experience.

• Strong understanding of protein structure and function

• Previous experience in protein engineering or computational protein design

• Strong publication record and experience contributing to research communities

• Strong programming skills in Python

Required PhD topics of study: Computational Biology, Computational Chemistry, Physics, Computer Science, Statistics, Applied Mathematics or related technical field, or equivalent practical experience

Other Preferred Qualifications

• Excellent communication, collaboration, and interpersonal skills.

• Experience with antibody structure and function.

• Experience in computational protein modeling software for proteins (e.g., Rosetta, Molecular Dynamics).

• Experience with machine learning libraries (e.g., pytorch, tensorflow, jax)

This postdoctoral position is located in South San Francisco, on site.  

For information about the Postdoctoral Program at Genentech, please go to: 

https://www.gene.com/careers/university-and-early-career/postdocs

The expected salary range for this position based on the primary location of California is $64,800 and $120,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.  This position also qualifies for the benefits detailed at the link provided below.

Benefits

Relocation benefits are available for this job posting.

Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.