Most people who don't get in fail the screening, not the CV. Five minutes here first: How to pass the micro1 AI interview with Zara.
What the work is
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.
Who gets hired
- 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.
The platform posted this on 15 Oct 2026.