Protein Design ML Scientist for Crop Trait Discovery

Syngenta Group; Durham (AR); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

Medical, dental & vision benefits

401k with company match

Paid vacation & holidays

Education assistance

Job summary

Syngenta Seeds in Durham, NC is seeking a Protein Design ML Scientist to advance agricultural trait discovery through state-of-the-art ML for computational protein engineering. You'll implement predictive models and work with experimentalists to optimize variant libraries amid limited data.

PhD-level candidates with biomolecular ML experience will collaborate across teams, leveraging Python, PyTorch/JAX, and HPC workflows to drive next-generation traits to the field.

Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Biochemistry, Biophysics, or related field with 1+ year protein sequence/structure modeling experience.
• Hands-on ML model work for protein design, variant library generation, or protein property prediction.

Responsibilities

• Develop scalable workflows for variant design and property prediction.
• Implement and optimize biomolecular ML models and protein language models.
• Collaborate with wet-lab teams to design variant libraries.
• Use active learning and Bayesian optimization to integrate results.
• Translate ML concepts for technical and non-technical audiences.
• Monitor advances in protein design and evaluate new tools.

Skills

Protein design

Python

Deep learning

PyTorch

JAX

Education

Ph.D. in Bioinformatics

Biochemistry/Biophysics

Tools

PyTorch

JAX

Docker

Rosetta

Job description

Syngenta Seeds in Durham, NC is seeking a Protein Design ML Scientist to advance agricultural trait discovery through state-of-the-art ML for computational protein engineering. You'll implement predictive models and work with experimentalists to optimize variant libraries amid limited data.

PhD-level candidates with biomolecular ML experience will collaborate across teams, leveraging Python, PyTorch/JAX, and HPC workflows to drive next-generation traits to the field.