We are looking for a researcher with a strong understanding of ML theory and who is skilled in developing novel deep-learning approaches to drug discovery and development. This will be a healthy mix of novel ML research with a component of ML Ops.

This is an opportunity to join a solid and tenured Biotech driven by an elite scientific leadership team with incredible resources to computation as a key pillar of the organization. Work in a creative environment and impact ML research and patient populations with serious unmet needs.

Opportunity to:

Work with a stellar computational team and a biotech that values computational sciences in an interdisciplinary setting with excellent resources.
Develop state-of-the-art Deep Learning approaches to solve long-standing problems in Biology.
Build novel architectures.
Develop highly sophisticated models to reduce the time and cost required to develop novel therapeutics.
Collaborate with experts in Computational Biology, Computational Chemistry, and Software Engineering.

We are looking for:

Advanced Degree in Computer Science, Mathematics, Physics, or related quantitative discipline.
Strong background in Mathematics with a focus on areas relevant to Machine Learning (Linear Algebra, Calculus, Statistics, and Probability Theory)
Drug Discovery/Development experience developing new ML and deep learning approaches.
Experience working with protein structure and folding sequence data.
Formal training in Deep Learning and experience with one or more of the following: Graph, Neural Networks, Transformers, Diffusion Models
Proven record of productivity and independence in the field of Deep Learning as evidenced by scientific publications or publicly available projects

You will stand out:

If you've worked with antibody drug discovery

*Must be authorized to work in the US.

Precision BioPartners

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