Bioinformatics / Computational Genomics Expert

We are looking for experts in Bioinformatics and Computational Genomics to develop challenging and realistic genomics tasks along with reference solutions for GeneBench Pro. In this role, you will create computational biology problems that require AI agents to interpret biological data, write and execute code, navigate scientific files, and generate objectively verifiable results. The tasks you design should mirror authentic bioinformatics workflows rather than isolated biology questions, ensuring they are scientifically meaningful and suitable for advanced AI evaluation.

Key Responsibilities:
- Design innovative, model-challenging tasks in computational genomics and bioinformatics.
- Develop tasks that assess higher-order scientific judgment, including managing ambiguous or noisy data, detecting artifacts, choosing appropriate analytical methods, revising assumptions based on intermediate findings, and deciding when conclusions are ready.
- Construct tasks using realistic scientific data formats such as FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, sequence annotations, expression data, and variant data (germline or somatic).
- Create multi-step analyses leveraging Python, command-line tools, and established bioinformatics libraries.
- Produce clear task specifications, input datasets, expected output formats, and deterministic or objectively verifiable ground truths.
- Develop expert reference solutions and reproducible computational workflows that operate within the provided Python-based environment.
- Validate that tasks are scientifically accurate, solvable with the provided information, and sufficiently challenging for cutting-edge AI models.
- Design robust grading criteria that differentiate scientifically correct solutions from superficially plausible ones.
- Ensure all deliverables are well documented, reproducible, and client-ready.
- Maintain high quality and throughput while incorporating feedback from reviewers.
- Communicate progress, challenges, and scientific or technical needs effectively to project leads and reviewers.

Required Qualifications:
- Ph.D., postdoctoral experience, or equivalent research background in Bioinformatics, Computational Biology, Genomics, Computational Genetics, or a closely related field.
- Strong hands-on programming skills in Python.
- Experience analyzing biological sequence or genomics datasets.
- Comfortable working in Linux and command-line computational environments.

Preferred Qualifications and Benefits:
- Experience with genomics workflows such as variant analysis, transcriptomics, sequence analysis, phylogenetics, population genetics, functional genomics, or clinical genomics.
- Familiarity with common bioinformatics libraries and tools including Biopython, pandas, NumPy, SciPy, samtools, bcftools, BLAST, PLINK, or equivalents.
- Proven ability to develop reproducible scientific pipelines.
- Experience evaluating AI or large language model systems on computational scientific tasks.
- Strong understanding of the experimental and biological context underlying computational analyses.
- Bonus points for experience with AI or coding agents, designing benchmark datasets or automated graders, publications in computational genomics or bioinformatics, and working with Docker or containerized scientific workflows.

Offer Details:
- Commitment: 40 hours per week with a required 4-hour overlap with Pacific Standard Time (PST).
- Engagement Type: Contractor/freelancer position (no medical benefits or paid leave).
- Contract Duration: 6 weeks.

This opportunity is ideal for candidates passionate about advancing AI capabilities in genomics through rigorous, scientifically grounded task design and solution development.