Role & responsibilities

- Design novel, model-challenging tasks in computational genomics and bioinformatics.

- Design tasks that test higher-order scientific judgment, including handling ambiguous or messy data, iidentifying 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.

Qualifications Required

- 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.

Preferred candidate profile

- 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.

- Robust understanding of experimental and biological context behind computational analyses.

📌 Bioinformatics / Computational Genomics Expert (Gurugram)
🏢 Crossing Hurdles
📍 Gurugram