Overview In this role you will advance generative AI methods for biomolecule design and optimization. You will work within Regeneron's tech-dev research team to bridge AI with therapeutic development in multiple diseases. You'll train and fine-tune models using diverse experimental data and contribute to closed-loop AI collaborations with wet-lab and clinical teams. This position offers meaningful impact in a fast-growing, science-driven company focused on patient outcomes.
Compensation / Benefits- health and wellness programs
- 401(k) company match
- equity awards
- paid time off
- paid leaves (e.g., parental leave)
- bonus opportunities
Responsibilities- Apply state-of-the-art generative AI to biomolecule design (proteins, antibodies, small molecules, nucleic acids)
- Train, fine-tune, and optimize models using curated and encoded experimental datasets
- Incorporate feedback from downstream experimental validation into model learning
- Collaborate with web lab teams and clinicians for closed-loop AI model development and inference
Key requirements- 2+ years of experience applying AI to biomolecule research (proteins, antibodies, or other molecules)
- PhD in Computational Biology, Bioengineering, Bioinformatics, Systems Biology, Computer Sciences, Mathematics, Engineering, or related field
- Familiar with cutting-edge generative AI foundation models for biomolecules
- Proficiency in programming languages such as Python, R, Perl, Java, or Linux
- self-motivated
- team-oriented
- collaborative research approach
- generative AI foundation models for biomolecules
- data curation, distillation, encoding; model learning and adaptation with feedback data
