Co-op, AI for Protein Design
Core
PhD-level co-op contributing to applied ML research in protein engineering, including generative protein design, antibody engineering, and wet-lab-informed model iteration.
Role type
PhD co-op machine learning researcher (protein design)
Builds
Generative and predictive models for protein and antibody design; workflows linking model predictions to wet-lab feedback; datasets and benchmarks for domain-specific and general AI research.
Domain
Life Sciences / Protein Engineering / Machine Learning
Deliverable
production ML models
Required skills
Python, PyTorch, JAX, machine learning, computational biology, protein engineering, biological sequence/structure/assay data analysis
Preferred skills
protein language models, diffusion or flow-based models, antibody design, developability, wet-lab validation concepts, active learning workflows
Technologies
PyTorch, JAX
Responsibilities
Research generative and predictive models for protein and antibody design; analyze experimental datasets to evaluate model outputs; prototype workflows linking model predictions and wet-lab feedback; build datasets and benchmarks; share results through code, notebooks, and presentations.
Seniority
PhD student (Co-op)
