Clinical, Microbiome & Translational Research Scientist (PhD)
micro1 · Remote – worldwide
- Salary
- Not stated
- Posted
- 12d ago
- Source
- Himalayas
Job description
Job Title: Clinical, Microbiome & Translational Research Scientist (PhD)
Job Type: Contractor
Location: Remote(Worldwide)
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
Key Responsibilities
• Design and write challenging, expert-level scientific problems in microbiome/metagenomics, clinical and translational bioinformatics, and related life sciences, with clear, verifiable solutions.
• Review and evaluate AI model outputs for scientific accuracy, rigor, and depth of reasoning, catching subtle errors non-specialists would miss.
• Develop detailed rubrics and reference answers grounded in primary literature and established methodology.
• Apply domain expertise across areas such as 16S and shotgun metagenomics, virome/host-microbiome analysis, biomarker discovery, clinical genomics, and omics-driven precision medicine.
• Provide clear written explanations of your reasoning so other experts can follow and validate it.
• Meet quality standards through iterative feedback and peer review.
Required Qualifications (MUST)
• PhD in Microbiology, Bioinformatics, Computational Biology, Biomedical Sciences, Immunology, Epidemiology, or a closely related field.
• Hands-on research experience in an academic or industry lab (wetlab experience is a plus).
• Professional written and spoken English (C1 or higher).
Preferred Skills
• Postdoctoral or industry research experience in microbiome, clinical, or translational research.
• Publication record, ideally first-author papers in relevant journals.
• Microbiome tools: QIIME2, Kraken2, MetaPhlAn, HUMAnN, MAG assembly/binning, virome analysis.
• Clinical/translational: TCGA, UK Biobank, biomarker discovery, survival analysis, EHR + omics integration, oncology/immunology genomics.
• Statistics and ML for high-dimensional biological data.
• Programming: Python and/or R (required in practice), Bash, workflow tools.
• Experience reviewing, benchmarking, or writing scientific content.
Originally posted on Himalayas
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