Bioinformatics Intern - Protein Design

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. We invite you to help shape the future of agriculture and play a role in safely feeding the world while caring for our planet.
Syngenta's Bioinformatics Team is seeking a Protein Design Intern in Durham, NC. This internship role will be part of a high-performance scientific team, developing cutting-edge skills in computational protein design to deliver innovative solutions for agricultural biotechnology.
As part of Syngenta's Emerging Talent Program, you will gain hands-on experience, exposure to day-to-day business operations, and opportunities to apply your academic knowledge to real-world challenges while developing your professional skills.
Duration: May 2027 - August 2027
Role Purpose:
Apply computational protein design methods to generate novel protein candidates and minibinders to selected targets.
Optimize workflows that integrate protein design, structure prediction, and ranking approaches to identify promising candidates.
Evaluate designed protein variants using sequence- and structure-based analyses.
Accountabilities:
Leverage open-source protein design and structure prediction workflows using tools such as ProteinMPNN, BoltzGen, and Boltz-2.
Design, rank, and filter protein candidates based on predicted structure, interface quality, and computational metrics.
Perform structural analysis and annotation of designed proteins and protein-protein interfaces.
Test and run computational protein design tools in Linux, HPC, or cloud-based environments such as AWS.
Develop Python/Bash scripts for data processing, workflow automation, and visualization.
Document workflows, create user guides and READMEs, and present findings to cross-functional teams.
Collaborate with and take guidance from other scientists to refine design strategy based on biological insights.
Summarize design results in clear reports, visualizations, and recommendations for follow-up testing.
Required Qualifications:
Education:
Current MS or PhD student in Bioinformatics, Computational Biology, Structural Biology, Biochemistry, Computer Science, or related field.
Technical:
Proficiency in Python and basic Bash scripting.
Basic understanding of protein structure concepts, including protein domains, structural alignment, and protein-protein interfaces.
Familiarity with protein structure prediction methods such as Boltz-2 or AlphaFold.
Familiarity with generative protein design or sequence design tools such as RFdiffusion or ProteinMPNN.
Familiarity with protein structure visualization tools (PyMOL).
Experience with Linux/Unix command-line environments.
Analytical:
Ability to work with large datasets and implement reproducible computational workflows.
Strong problem-solving skills and attention to detail.
Effective written and verbal communication skills.
Desired Qualifications:
Experience evaluating protein-protein interfaces using structural or energetic metrics (e.g. PyRosetta).
Knowledge of protein databases such as PDB, UniProt, AlphaFoldDB, or ESM Metagenomic Atlas.
Experience with HPC or cloud computing environments, such as AWS.
Experience with workflow automation, containerized tools, or reproducible software environments.
Self-motivated with ability to work independently and collaboratively.
Enthusiasm for learning new computational methods and tools.
Experience presenting technical work to diverse audiences.

Employment type
Intern

Work arrangement
No