[UHS8CUGM]-Bioinformatics / Computational Genomics Expert

Hello,

Greetings from ZettaMine!!!

Freelancing Opportunity :- We are currently hiring Bioinformatics / Computational Genomics Experts for a short-term AI training and evaluation project across Argentina, Bangladesh, Brazil, Colombia, Egypt, Nigeria, Ghana, India, Indonesia, Turkey, Chile, Peru, Sri Lanka, Saudi Arabia, Nepal, and Mexico .

Role: Bioinformatics / Computational Genomics Expert

Experience: Ph.D., Postdoctoral Experience, or equivalent research experience in Bioinformatics, Computational Biology, Genomics, or Computational Genetics

Mode of Work: Remote

Engagement: Full-Time – 40 Hours/Week

Description

We are seeking Bioinformatics and Computational Genomics Experts to design challenging, agentic genomics tasks and reference solutions for GeneBench Pro .

The work involves creating realistic computational biology problems that require AI agents 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.

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 within the provided Python-based environment.

Responsibilities

• Design novel, model-challenging tasks in computational genomics and bioinformatics.
• Create tasks that test higher-order scientific judgment, including handling ambiguous or messy data and identifying artifacts.
• Select appropriate analytical approaches and revise assumptions based on intermediate results.
• Design tasks using realistic scientific data such as FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, sequence annotations, expression data, germline or somatic variant data , and 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.

Core Domains

• Computational Genomics
• Bioinformatics
• Computational Biology
• Genomics
• Computational Genetics
• Sequence Analysis
• Variant Analysis
• Transcriptomics
• Population Genetics
• Functional Genomics
• Clinical Genomics

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 in Python .
• Experience analyzing biological sequence or genomics datasets.
• Comfortable working in Linux/command-line computational environments .
• Strong understanding of biological and computational analysis workflows.
• Ability to develop reproducible scientific computational workflows.

Preferred

• 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 such as Biopython, pandas, NumPy, SciPy, samtools, bcftools, BLAST, PLINK , or equivalent tools.
• Experience developing reproducible scientific pipelines.
• Experience evaluating AI/LLM systems on computational scientific tasks.
• Strong understanding of the experimental and biological context behind computational analyses.

Bonus Points

• Experience with AI agents or coding agents .
• Experience designing benchmark datasets or automated graders.
• Publications involving computational genomics or bioinformatics.
• Experience with Docker/containerized scientific workflows .
• Experience developing scientific benchmarks or AI evaluation datasets.

Availability

• Full-Time – 40 Hours per Week
• Minimum 4 hours of PST overlap per day
• Immediate availability preferred

Interested candidates kindly share your updated CV to [email protected]

Thanks & Regards,

RaviTeja K

ZettaMine