You will create realistic computational biology problems that require an AI agent to interpret biological data, write and execute code, work across scientific files, and produce objectively verifiable outputs. Tasks should reflect authentic genomics and bioinformatics workflows rather than standalone biology questions.

Engagement type : Contractor assignment/freelancer (no medical/paid leave).

Environment

Each GeneBench Pro problem is a self-contained scientific analysis. Agents receive an isolated workspace with a short prompt, data files, and a standard bioinformatics stack including Python, scientific computing libraries, and basic genomics packages such as PLINK 2.0. Reference solutions must run in this Python-based environment.

• Design novel, model-challenging tasks in computational genomics and bioinformatics.
• Design tasks that test higher-order scientific judgment, including handling ambiguous or messy data, identifying artifacts, selecting appropriate analytical approaches, revising assumptions based on intermediate results, and determining when conclusions are decision-ready.
• Build tasks involving realistic scientific data such as FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, sequence annotations, expression data, germline or somatic variant data, or other genomics artifacts.
• Develop tasks requiring multi-step analysis using Python, command-line tools, or established bioinformatics libraries.
• Create clear task specifications, input datasets, expected output schemas, and deterministic or objectively verifiable ground truths.
• Develop expert reference solutions and reproducible computational workflows that run in the provided Python stack.
• Validate that tasks are scientifically correct, solvable from the supplied information, and sufficiently challenging for frontier AI models.
• Design robust grading criteria that distinguish scientifically correct solutions from superficially plausible outputs.
• Ensure all deliverables are well documented, reproducible, and client-ready.
• Maintain high quality and throughput while incorporating reviewer feedback.
• Communicate progress, blockers, and scientific or technical requirements to project leads and reviewers.

• Ph.D., postdoctoral experience, or equivalent research experience in Bioinformatics, Computational Biology, Genomics, Computational Genetics, or a closely related discipline.

Work arrangement: Fully remote

Applicant eligibility: 12 eligible countries

Location : Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam.