[UHS8CUGM] Bioinformatics / Computational Genomics Experts

Hello,

Greetings from ZettaMine!!!

We are hiring Bioinformatics / Computational Genomics Experts for a short-term AI Training & Evaluation project across: India

Role: Bioinformatics / Computational Genomics Expert

Experience: Ph.D., Postdoctoral Experience, or Equivalent Advanced Research Experience

Mode: Remote

Engagement: Contractor / Short-Term Contract

Start: Immediate

Mandatory Eligibility Criteria

Technical Qualification:

• Strong programming skills in Python and relevant scientific computing or bioinformatics libraries.
• Experience working in Linux or terminal-based environments.
• Strong knowledge of bioinformatics, computational genomics, computational biology, genomics, and computational genetics workflows.
• Experience analyzing biological sequence, genomic, transcriptomic, variant, or other computational biology datasets.
• Ability to independently implement, test, debug, and validate computational bioinformatics workflows.
• Strong understanding of biological data quality, analytical assumptions, artifacts, numerical accuracy, scientific validation, and reproducibility.
• Ability to develop rigorous scientific tasks with clearly defined inputs, expected outputs, ground truths, and evaluation criteria.
• Experience working with FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, sequence annotations, expression data, and germline or somatic variant data.
• Ability to develop and validate computational workflows involving variant analysis, transcriptomics, sequence analysis, phylogenetics, population genetics, functional genomics, and clinical genomics.
• Ability to develop multi-step analyses using Python, command-line tools, and established bioinformatics libraries.
• Ability to identify artifacts, handle ambiguous or messy biological data, and select appropriate analytical approaches.
• Ability to validate scientific outputs for biological consistency, computational accuracy, and reproducibility.

Educational Qualification:

Mandatory: Ph.D., postdoctoral experience, or equivalent advanced research experience in Bioinformatics, Computational Biology, Genomics, Computational Genomics, Computational Genetics, or another closely related discipline.

Preferred: Advanced research or professional experience in Computational Genomics, Bioinformatics, Sequence Analysis, Variant Analysis, Transcriptomics, Phylogenetics, Population Genetics, Functional Genomics, Clinical Genomics, or related fields.

Availability:

• Full-Time – 40 Hours per Week.
• Minimum 4 hours of PST overlap per day.
• Ability to work remotely on a short-term AI training and evaluation project.
• Immediate availability preferred.
• Ability to collaborate with project reviewers and incorporate feedback.
• Availability according to project requirements and deadlines.

Others:

• Personal laptop/desktop and stable high-speed internet.
• Strong written and verbal communication skills.
• Strong hands-on experience with Python and scientific computing.
• Experience working with bioinformatics and terminal-based computational environments.
• Familiarity with bioinformatics libraries and tools such as Biopython, pandas, NumPy, SciPy, samtools, bcftools, BLAST, PLINK, or equivalent tools.
• Experience developing reproducible scientific and bioinformatics pipelines.
• Strong understanding of the experimental and biological context behind computational analyses.
• Experience with Docker/containerized scientific workflows is preferred.
• Experience with AI agents, coding agents, or AI/LLM evaluation systems is advantageous.
• Experience designing benchmark datasets, automated graders, scientific benchmarks, or AI evaluation datasets is preferred.
• Publications involving computational genomics or bioinformatics are advantageous.
• Strong attention to scientific accuracy, documentation, biological validity, and reproducibility.

What You’ll Work On:

• Design authentic, multi-step Bioinformatics and Computational Genomics tasks based on realistic scientific and computational workflows.
• Design novel, model-challenging computational genomics and bioinformatics tasks for GeneBench Pro.
• Translate authentic genomics and bioinformatics workflows into self-contained scientific analysis environments.
• Prepare realistic scientific datasets such as FASTA/FASTQ, VCF, BAM/SAM, BED, TSV/CSV, sequence annotations, expression data, and germline or somatic variant data.
• Implement expert solutions using Python, command-line tools, scientific computing libraries, and relevant bioinformatics tools.
• Create tasks involving variant analysis, transcriptomics, sequence analysis, phylogenetics, population genetics, functional genomics, and clinical genomics.
• Develop tasks that test higher-order scientific judgment, including handling ambiguous or messy biological data and identifying artifacts.
• Select appropriate analytical approaches and revise assumptions based on intermediate scientific results.
• Develop expert reference solutions and reproducible computational workflows that execute within the provided Python-based environment.
• Create clear task specifications, input datasets, expected output schemas, and deterministic or objectively verifiable ground truths.
• Develop robust automated grading criteria that distinguish scientifically correct solutions from superficially plausible outputs.
• Validate that tasks are scientifically correct, solvable using the supplied information, reproducible, and sufficiently challenging for frontier AI models.
• Ensure all computational workflows and deliverables are well documented, reproducible, and client-ready.
• Develop benchmark tasks that evaluate whether AI agents can reason through bioinformatics and genomics problems, interpret biological datasets, write and execute code, operate command-line and genomics tools, troubleshoot computational workflows, and produce accurate and objectively verifiable scientific outputs.

Interested candidates kindly share your updated CV and Google Scholar profile/link to raviteja.k@zettamine.com

Thanks & Regards,

Raviteja K

ZettaMine