Lead Computational Biologist – Machine Learning

San Francisco, California

Machine Learning

Permanent

Our client are a growing Biotech startup and they are hiring a Lead Computational Biologist to join the team on a hybrid working model in South San Francisco. The successful candidate will enjoy a key role in their AI/Machine Learning team and will develop start of the art multi-omics computational biology methods and ML Models for the company’s unique drug discovery platform.

Responsibilities

Develop Machine Learning methods to generate and evaluate hypothesis for drug development from high content biopharma omics.
Work with a team of Bioinformatics, Cheminformatics, Machine Learning Engineers and others to synthesize data, validate methods and functionality.
Process research papers, evaluate & integrate commercial & publically available frameworks and methods.
Industrialize multi-omics computational approaches and proof of concept to implementation and scale them with robust ML engineering pipelines.

Skillset

PhD or Master’s degree in Computational Biology, Bioinformatics or similar.
Strong knowledge of molecular biology, proteomics and / or genomics.
Strong hands-on experience developing Machine Learning methods for omics data.
Expertise in current computational tools required to process and analyze a variety of biopharma datasets.
Practical understanding of Machine Learning fundamentals, models and algorithms.
Expertise in modern AI tech stack.