PhD-Level Computational Biologist -- Design Data-Centric Benchmarks for AI ModelsMercor • San Francisco, CA, US
PhD-Level Computational Biologist Design Data-Centric Benchmarks for AI Models
Mercor • San Francisco, CA, US
[job_card.variable_days_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]Hands-on experience analyzing sequencing or omics datasets (e.g., RNA-seq, WGS, mass spec) Proficient with bioinformatics tools and formats (e.g., BLAST, samtools, DESeq2, FASTA / FASTQ / BAM) Comfortable coding in Python, R, or bash, and working in Jupyter notebooks Understanding of biological experiment design and lab-to-data nuances (e.g., batch effects) Advanced degree (MS, PhD) or research background in computational biology, genomics, or bioinformatics Remote and asynchronous — set your own schedule Expected commitment : 15–20 hours / week Project duration : ~1 month Potential for additional projects based on performance and interest $65–85 / hour depending on experience and geography Paid weekly via Stripe Connect Structured as a freelance contract — independent contractor status Submit your resume to get started Qualified applicants will complete a short form assessing technical experience Follow-up steps may include a sample task or review call Responses typically within 3–5 business days Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey. Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI.
Job Description
Job Description
1. Role Overview
Mercor is seeking computational biology experts to contribute to a unique project with a top-tier AI research organization. This short-term initiative challenges AI models with hidden-answer “mystery problems” grounded in real biological data. Experts will design, validate, and anonymize complex datasets to evaluate model reasoning capabilities, not lookup accuracy. This is a compelling opportunity for data-driven life scientists to shape next-generation AI evaluation benchmarks.
2. Key Responsibilities
- Design biologically grounded problems with a single correct answer and ≥20 plausible distractors
- Identify, download, and preprocess datasets from public repositories (e.g., GEO, SRA, NCBI)
- Subsample and anonymize datasets to prevent metadata-based inference
- Independently validate solutions through custom analysis pipelines and visualizations
- Operate within technical constraints (e.g., file size, task time limits)
3. Ideal Qualifications
4. More About the Opportunity
5. Compensation & Contract Terms
6. Application Process
7. About Mercor
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