Protein Design Scientist
Core
Develop and implement state-of-the-art ML algorithms for computational protein engineering to drive agricultural trait discovery and deliver next-generation traits.
Role type
Senior IC machine-learning scientist (protein design)
Builds
Predictive models, active learning workflows, and variant libraries for protein engineering
Domain
Agricultural biotechnology / Computational protein design
Deliverable
production ML models
Required skills
Protein language modeling, generative models, co-evolutionary architectures, 3D structure prediction, active learning, Bayesian optimization, Python, deep learning frameworks (PyTorch, JAX)
Preferred skills
Protein structural information integration, structure prediction tools (AlphaFold, Boltz), structure-aware design methods (ProteinMPNN, GNNs), physics-based modeling (Rosetta, MD), cloud/HPC environments, containerized workflows (Docker, Singularity, Nextflow)
Responsibilities
Develop biological hypotheses and scalable computational workflows for variant design; Implement and optimize biomolecular ML models; Partner with wet-lab teams to design variant libraries; Integrate experimental screening results into iterative design cycles; Analyze computational and experimental data to guide design strategies; Monitor developments in protein design research
Seniority
Senior, hands-on IC