Computer Science (STEM)

Engagement Details

Key Responsibilities

• Design challenging, realistic agentic scientific workflows across the life sciences.
• Create tasks requiring multiple computational steps rather than single-script or simple question-and-answer solutions.
• Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
• Build tasks requiring agents to inspect data, select appropriate methods, execute analyses, troubleshoot problems, and synthesize results.
• Create reproducible expert solutions and objectively verifiable ground truths that run in the provided sandbox environment.
• Design robust automated or semi-automated grading criteria.
• Ensure tasks measure scientific reasoning and execution rather than memorization.
• Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
• Ensure tasks are self-contained and executable in controlled, network-isolated computational environments.
• Maintain high quality and throughput while responding effectively to reviewer feedback.

Qualifications Required

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

Preferred Qualifications

• Expertise in one or more areas, including bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, computational biochemistry, 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.