AI-First Protein Designer for Crop Traits

Syngenta Seeds; Durham (NC); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Flexible work options

Full Benefits Package

401k with company match

Paid vacation and holidays

Job summary

Syngenta Seeds in Durham, NC seeks a PhD-level Protein Design Scientist to drive AI-first trait discovery, leveraging protein language models and generative design to explore sequence-function relationships.

You will collaborate with wet-lab teams, adapt open-source models, and translate ML outputs into actionable insights for crop improvements. This role blends computational biology with hands-on biological work in a fast-moving AgTech environment.

Qualifications

• PhD with +1-year experience in bioinformatics or related field focusing on protein sequence/structure modeling.
• ML models applied to protein design, variant libraries, or property prediction.
• Deep understanding of protein sequence-structure-function relationships.
• Ability to translate complex ML outputs to actionable insights for stakeholders.
• Strong collaboration with wet-lab teams and clear communication.

Responsibilities

• Design and optimize computational workflows for large-scale variant design and property prediction.
• Deploy and fine-tune biomolecular ML models to support trait pipelines.
• Collaborate with wet-lab teams to integrate experimental data into design loops.
• Communicate complex ML concepts clearly to technical and non-technical stakeholders.
• Stay updated with protein design literature and bring new tools to the team.

Skills

Protein design

ML for proteins

Python

Deep learning

pLMs

Bayesian optimization

Education

PhD in bioinformatics / computational biology / biochemistry / biophysics

Tools

PyTorch

JAX

AlphaFold

Foldseek

Docker

Job description

Syngenta Seeds in Durham, NC seeks a PhD-level Protein Design Scientist to drive AI-first trait discovery, leveraging protein language models and generative design to explore sequence-function relationships.

You will collaborate with wet-lab teams, adapt open-source models, and translate ML outputs into actionable insights for crop improvements. This role blends computational biology with hands-on biological work in a fast-moving AgTech environment.