Clinical, Microbiome & Translational Research Scientist (PhD)
micro1
Удалённая работа
- Местоположение
- Remote (Worldwide)
- График
- Contractor
- Опубликовано
- 16 окт. 2026 г.
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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