Scientist I / Scientist II, Computational Protein Generation

📋 Description

• Model de novo protein generation and optimize with in‑loop data.
• Define, implement, and benchmark in silico metrics for designs.
• Benchmark foundation models and guide their application.
• Propose new therapeutic strategies using de novo tools.
• Collaborate across teams to drive design–build–test–learn cycles.
• Build production‑quality tools and integrate AI agents to accelerate iterations.

🎯 Requirements

• PhD in Computational Biology, Biophysics, CS, or related.
• 0–2 years experience applying ML methods to protein design or prediction.
• Hands-on ML/generative modeling for protein design; RFDiffusion, ProteinMPNN experience.
• Python proficiency and production‑grade code experience.
• Experience designing, running, and interpreting benchmarks for computational methods.
• Familiarity with protein therapeutic modalities (antibodies, mini‑proteins, VHHs, peptides, enzymes).

🎁 Benefits

• Hybrid work arrangement in Somerville, MA.
• Collaborative ML and biology team.
• Exposure to cutting‑edge protein design platforms.
• Opportunities for professional growth and learning.