Scientist / Senior Scientist, Computational Biology

Syenex • Evanston, IL

35d

About The Position

The Scientist / Senior Scientist in Computational Biology will build the computational backbone of the company’s R&D engine, working at the intersection of computational and experimental biology. This hands-on, cross-functional role leads high-throughput, library-based discovery campaigns, integrates machine learning and AI into biomolecular design, and develops automation and internal software to accelerate research and operations.

The role partners closely with bench scientists to turn data into improved molecules, and works directly with the Co-founder and CSO on dedicated projects. It encompasses computational method development, biomolecular engineering and design, research software, data analysis and visualization, and guidance on the development, use, and validation of machine-learning tools across R&D. The successful candidate will also support thoughtful enterprise AI adoption throughout operations and use AI tools in their own experimental planning, tool development, and data interpretation.

Requirements

• MS or PhD in a relevant scientific, engineering, and/or data science discipline.
• Dedicated training or experience in contemporary machine-learning methodology, best practices, and applications.
• At least 3 years of relevant industry experience, including high-throughput biology research, machine learning for R&D, and automation of data and design workflows.
• Facility with enterprise AI tools, including but not limited to Claude Code, and computational biomolecular design packages employing AI/ML.
• Specific experience in biotechnology.
• Ability to thrive in a dynamic, collaborative research environment while balancing scientific rigor with rapid iteration.
• Demonstrated curiosity, creativity, and ownership in driving projects forward.
• Strong problem-solving skills and ability to navigate ambiguity in a fast-paced research environment.
• Ability to work independently while collaborating effectively across computational and bench science teams.

Responsibilities

• Work directly with the Co-founder and CSO on dedicated projects.
• Lead computational aspects of method development, including high-throughput, library-based discovery and refinement campaigns such as binder protein discovery and optimization.
• Integrate machine learning and AI into protein, DNA, and RNA engineering, iteration, and product-development workflows, including computational prediction of biomolecular structures.
• Collaborate with the R&D team to design and deliver customized automation, data analysis, data visualization, and biomolecular design tools.
• Partner with bench scientists to generate high-quality, analysis-ready data and rapidly feed results into subsequent experiments.
• Build and maintain custom internal software packages for research and operations, including automated workflows, DNA and library design, and data analysis.
• Advise on best practices for developing, using, and validating machine-learning tools across R&D.
• Facilitate thoughtful adoption and deployment of enterprise AI tools throughout operations, and use them for experimental planning, tool development, and data interpretation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level