About the Role
We are looking for a Computational Life Sciences Specialist with strong Python and scientific programming experience to develop complex, realistic tasks for AI agents working across the life sciences. You will design multi-step scientific workflows where AI agents must analyze data, write and execute code, troubleshoot results, and produce scientifically valid outputs. This role focuses on evaluating authentic scientific reasoning and execution rather than simple question answering, with an emphasis on reproducibility, objective validation, and computational reliability.
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Key Responsibilities
- Design complex scientific workflows across computational life sciences that require multiple analytical and computational steps.
- Develop realistic scientific datasets, input files, instructions, constraints, and expected deliverables.
- Create tasks requiring AI agents to inspect data, select appropriate methods, execute analyses, and troubleshoot intermediate results.
- Implement reproducible expert solutions and objectively verifiable ground truths.
- Design robust automated or semi-automated grading criteria for scientific tasks.
- Validate scientific assumptions, calculations, code, intermediate outputs, and final results.
- Ensure task dependencies, data, and computational resources can be reliably packaged in controlled environments.
- Develop workflows using Python, command-line tools, scientific libraries, and relevant domain-specific software.
- Ensure tasks assess scientific reasoning and execution rather than memorization.
- Maintain high task quality and throughput while incorporating reviewer feedback.
Requirements
- PhD, postdoctoral experience, or equivalent research experience in Life Sciences or a closely related field.
- Strong Python programming skills with demonstrated experience in scientific computing.
- Experience conducting multi-step computational scientific analyses.
- Experience working with scientific datasets and computational tools.
- Ability to independently validate scientific reasoning, calculations, and computational outputs.
- Experience developing reproducible computational workflows and verifying expected results.
- Familiarity with scientific libraries, command-line tools, or domain-specific life sciences software.
- Experience in scientific research involving computational methods, data analysis, or scientific programming.
