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.
