Designs challenging computational genomics and bioinformatics tasks for AI benchmarking. Responsibilities include creating reproducible multi-step workflows using biological datasets, Python, command-line tools, and bioinformatics libraries; developing reference solutions, validation methods, grading criteria, and ground truths; troubleshooting scientific and computational issues; documenting deliverables; and communicating requirements and progress to project leads and reviewers.
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are seeking a Bioinformatics and Computational Genomics Specialist to design challenging, realistic scientific tasks and reference solutions for an AI benchmarking project. You will create multi-step genomics workflows that require AI agents to interpret biological data, write and execute Python code, use computational tools, troubleshoot intermediate results, and produce scientifically valid, objectively verifiable outputs.
The role is ideal for someone with advanced experience in bioinformatics, computational biology, genomics, or computational genetics, combined with strong Python programming skills and practical experience working with biological datasets.
WORK ENVIRONMENT: Isolated, reproducible Python-based computational environment with bioinformatics tools and libraries
Key Responsibilities
- Design novel, challenging tasks in computational genomics and bioinformatics that test advanced AI agent capabilities.
- Develop realistic, multi-step workflows involving biological datasets such as FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, expression data, and sequence annotations.
- Create tasks that require scientific judgment, including identifying data artifacts, handling ambiguity, selecting appropriate methods, and revising assumptions based on intermediate results.
- Prepare clear task specifications, input datasets, expected output schemas, and objectively verifiable ground truths.
- Develop expert reference solutions and reproducible computational workflows using Python, command-line tools, and bioinformatics libraries.
- Validate that tasks are scientifically accurate, solvable from the supplied information, and sufficiently challenging for advanced AI models.
- Design robust grading criteria that distinguish scientifically correct solutions from superficially plausible outputs.
- Ensure deliverables are reproducible, well documented, and suitable for client review.
- Incorporate reviewer feedback while maintaining high standards for quality and throughput.
- Communicate progress, blockers, and scientific or technical requirements to project leads and reviewers.
Requirements
- Ph.D., postdoctoral experience, or equivalent research experience in Bioinformatics, Computational Biology, Genomics, Computational Genetics, or a closely related discipline.
- Strong hands-on programming experience with Python.
- Practical experience analyzing biological sequence or genomics datasets.
- Experience working in Linux or command-line computational environments.
- Ability to independently validate scientific reasoning, computational methods, and analytical outputs.
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