Postdoctoral Fellow - Computational Biology / Machine Learning, Sterne-Weiler Lab

Genentech • South San Francisco, CA

140d • $110,000 - $120,000

About The Position

A position is available for a postdoctoral fellow to join the Genentech Computational Sciences (gCS) organization which uses data, by developing best in class computational methods, and applying them to the most relevant scientific problems across all stages of the pipeline. This position is based within the Sterne-Weiler Lab in Computational Biology / Discovery Oncology. The postdoctoral position is focused on developing and applying foundational AI models to investigate clinically relevant cancer vulnerabilities and their relationship with molecular context. Spanning functional genomics and large-scale clinical genomics, the postdoctoral fellow will build and train new models to understand the impact of mutation on protein structure and the role of genomic alterations on cancer cell state. While this position is computational, the project is highly collaborative, involving regular interaction with laboratory colleagues in the Discovery Oncology therapeutic area.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field.
• Demonstrated proficiency with Python, and machine learning libraries; pytorch, sklearn.
• Experience with transformer architectures, and interpretable AI methods and libraries, concept-bottleneck architectures, attribution packages: shap, captum, etc.
• Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics and transcriptomics, single-cell RNA-seq, Perturb-seq).
• Demonstrated ability to clearly and effectively communicate about complex bioinformatics problems to both technical and non-technical audiences; this should be both in written and verbal form, as evidenced by first-author publications in high-impact journals.
• Independent, highly motivated, and highly collaborative with the ability to work together with multi-disciplinary teams of computational and laboratory biologists.

Nice To Haves

• Background in cancer genomics and pre- and/or post-training of foundation models for biology is preferred.
• Passionate about working in a scientific environment, especially one that is related to drug discovery and development.
• Ability to prioritize, prototype and pressure-test new ideas to reduce time between iterations.
• Quick learner, curious about new areas and the opportunity to build expertise, and courageously take initiative to see ideas implemented.
• Able to perform at a high level in a fast changing and demanding environment.

Responsibilities

• Work closely with computational colleagues to build, train, and evaluate cutting edge AI models using large proprietary oncology datasets.
• Leverage multimodal high dimensional data to investigate relationship between heterogeneous cancer alterations and cancer cell states.
• Conduct exploratory research in a fast-paced setting with the potential for real impact on patients.
• Receive technical and scientific mentorship from computational and laboratory colleagues in the development and testing of biological hypotheses.
• Present at external scientific conferences and publish models and scientific insights in high-impact journals.

Benefits

• Relocation benefits are available for this job posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Chemical Manufacturing
• Education Level: Ph.D. or professional degree