Agentic Life Science Expert

Engagement: 3-Month Contract

Shift: 8 hours/day — 7:30 PM–11:30 PM fixed + 4 hours flexible

Experience: Ph.D., Postdoctoral, or equivalent research experience in Life Sciences

LinkedIn: Mandatory in CV

Role Overview

We are seeking Computational Life Sciences experts with strong scientific programming skills to develop complex, realistic tasks for Agentic Life Sciences. You will design tasks where AI agents independently navigate scientific data, write and execute code, use computational tools, troubleshoot intermediate results, and produce scientifically valid outputs.

Key Responsibilities

- Design challenging, realistic agentic scientific workflows across the life sciences.
- Create multi-step computational tasks requiring scientific reasoning and execution.
- Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
- Design tasks requiring agents to inspect data, select methods, execute analyses, troubleshoot problems, and synthesize results.
- Create reproducible expert solutions and objectively verifiable ground truths.
- Design robust automated or semi-automated grading criteria.
- Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
- Ensure tasks are self-contained,



reproducible, and executable in controlled, network-isolated environments.
- Maintain high quality and throughput while incorporating reviewer feedback.

Required Qualifications

- Ph.D., Postdoctoral, or equivalent research experience in Life Sciences.
- Strong computational and scientific programming experience.
- Solid Python programming skills.
- Experience performing multi-step computational scientific analyses.
- Ability to independently validate scientific reasoning and computational outputs.

Preferred Expertise

- Bioinformatics
- Computational Genomics
- Systems Biology
- Computational Neuroscience
- Biostatistics
- Computational Drug Discovery
- Computational Biochemistry
- Structural Biology
- Protein Engineering
- Computational Microbiology
- Scientific libraries and command-line tools
- Reproducible research pipelines
- Translating authentic research workflows into objectively gradable tasks

Bonus Points

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

📌 Life Science (India)
🏢 Sourcebae
📍 India