Senior Computational Biologist, AI‑Driven Biomolecular Design

Syenex, Inc; Evanston (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Syenex, Inc. is seeking a Scientist / Senior Scientist in Computational Biology to lead the computational backbone of our R&D engine. You will drive high-throughput discovery campaigns, apply ML to protein, DNA, and RNA engineering, and build automation and internal software to accelerate research and operations.

This hands-on, cross-functional role requires production-quality coding, collaboration with bench scientists, and the ability to turn data into better molecules at speed.

Qualifications

• MS or PhD in a relevant science, engineering, and/or data science discipline.
• 3+ years of industry experience in high-throughput biology and ML for R&D.
• Experience with enterprise AI tools such as Claude Code.
• Ability to work across computational and bench science teams.

Responsibilities

• Lead computational aspects of method development for high-throughput discovery campaigns.
• Integrate ML/AI into protein, DNA, and RNA engineering workflows.
• Develop and maintain internal software for data analysis and biomolecular design.
• Collaborate with bench scientists to ensure data quality and actionable outputs.
• Advise on best practices for ML tools in R&D and deployment of enterprise AI tools.
• Partner with R&D to deliver automation and data visualization tools.

Skills

Computational biology

Machine learning for biotech

High-throughput workflows

Automation of data workflows

Collaborative research

Production-quality coding

Education

MS or PhD in relevant field

Tools

Claude Code

Biomolecular design software

Automation tooling

Job description

Syenex, Inc. is seeking a Scientist / Senior Scientist in Computational Biology to lead the computational backbone of our R&D engine. You will drive high-throughput discovery campaigns, apply ML to protein, DNA, and RNA engineering, and build automation and internal software to accelerate research and operations.

This hands-on, cross-functional role requires production-quality coding, collaboration with bench scientists, and the ability to turn data into better molecules at speed.