Agentic Life Science Expert at Turing

Agentic Life Science Expert | Contractor | Worldwide Remote

Turing is looking for a Computational Life Sciences expert with strong scientific programming skills to design complex, realistic agentic tasks that evaluate whether AI systems can perform authentic multi-step scientific work — not just answer scientific questions.

About the Role

You will develop challenging, self-contained scientific workflows where AI agents must independently navigate data, write and execute code, use computational tools, troubleshoot intermediate results, and produce scientifically valid outputs. Tasks are executed in controlled, network-isolated computational environments and must be reproducible.

Key Responsibilities

• Design challenging, realistic agentic scientific workflows across the life sciences.
• Create multi-step computational tasks — not single-script or simple Q&A solutions.
• Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
• Build tasks requiring agents to inspect data, select methods, execute analyses, troubleshoot problems, and synthesize results.
• Create reproducible expert solutions and objectively verifiable ground truths within the sandbox environment.
• Design robust automated or semi-automated grading criteria.
• Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
• Maintain high quality and throughput while responding effectively to reviewer feedback.

Required Qualifications

• Ph.D., postdoctoral, or equivalent research experience in the life sciences.
• Strong scientific programming experience, particularly in Python.
• Experience performing multi-step computational scientific analyses.
• Ability to independently validate scientific reasoning and computational outputs.

Preferred Qualifications

• Expertise in bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, structural biology, protein engineering, or computational microbiology.
• Experience with scientific libraries and command-line tools.
• Experience creating reproducible research pipelines.
• Ability to translate authentic research workflows into bounded, objectively gradable tasks.

Bonus Points For

• Experience with AI agents, coding agents, or scientific AI systems.
• Experience building automated evaluation environments.
• Familiarity with Docker and Linux environments.
• Publications involving computational or data-intensive life sciences research.