Life Science

Sourcebae; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Sourcebae is seeking Computational Life Sciences experts to design and implement complex tasks for AI agents operating on scientific data. You will craft multi-step workflows, generate datasets, and ensure reproducible results in isolated environments.

The role requires Ph.D. or postdoctoral experience in Life Sciences, strong programming skills, and the ability to validate reasoning and outputs across diverse bioscience domains.

Qualifications

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

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.

Skills

Computational programming

Scientific programming

Multi-step analyses

Independent validation

Bioinformatics

Education

Ph.D./Postdoc in Life Sciences

Tools

Docker

Linux

Command-line tools

Bioinformatics libraries

Job description

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.
• 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
• Computational Drug Discovery
• Computational Biochemistry
• Structural Biology
• 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.