Microbiome & Translational Research Scientist - Remote
YO AI Labs · United States · US
Clinical Data Science
Remote
Not yet analysed
Demand65
Career growth60
Healthcare fit70
Remote potential100
5-year outlook
Compensation is likely project- or contributor-based and may vary widely by contract, expertise, and volume of work. Long-term earnings depend on sustained demand for expert AI-training and scientific evaluation work in specialized biomedical domains.
Clinical license
Not required
Applicant reach
narrow
Seniority
mid
Employment type
–
Date found
2026-11-08
Intelligence details
Flexible work details
- Engagement type
- Contract
- Hours
- Variable hours
- Eligible countries
- United States
- Rate period
- Annual
Why this was classified this way
- Contractor
Listing via Himalayas.
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Worth considering for PhD-trained clinician-researchers with strong microbiome, bioinformatics, or translational research backgrounds who want flexible remote AI-related work. General clinicians without advanced research/data skills are unlikely to be competitive.
Who should apply
Physician-researchers, IMGs, or healthcare graduates with PhD-level training in microbiology, bioinformatics, computational biology, immunology, epidemiology, or translational research; candidates with Python/R, metagenomics, clinical genomics, and scientific writing experience.
CV angle
Frame real clinical and research experience around microbiome/metagenomics analysis, bioinformatics pipelines, Python/R, statistical modeling, biomarker discovery, clinical genomics interpretation, publications, peer review, and scientific writing. Emphasize experience evaluating scientific evidence, developing rigorous research questions, and documenting reproducible analytical methods without overstating AI-specific experience.
Skills to highlight
- Microbiome and metagenomics analysis
- Bioinformatics pipelines and clinical genomics tools
- Python and R programming
- Statistical analysis and machine learning
- Biomarker discovery and high-dimensional biological data analysis
- Scientific writing and literature review
- AI output evaluation and peer review
- Translational research and clinical data interpretation
Role summary
A remote, expert-contributor research role supporting an AI training project by creating scientific problems, evaluating AI-generated scientific outputs, analyzing microbiome and clinical genomic datasets, and documenting findings with rigorous research standards.
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