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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 the life sciences, with clear, verifiable solutions.
- Review and evaluate AI model outputs for scientific accuracy, rigor, and depth of reasoning, catching subtle errors that non-specialists would miss.
- Develop detailed rubrics and reference answers grounded in primary literature and established experimental and computational methodology.
- Apply your domain expertise in areas such as genomics, transcriptomics and single-cell/spatial omics, epigenomics, proteomics and metabolomics, microbiome and metagenomics, structural biology, drug discovery, systems biology, and clinical/translational research.
- Bridge experimental and computational perspectives: assess whether a proposed experiment, analysis pipeline, or interpretation is scientifically sound.
- 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
- Completed PhD in Biology, Molecular Biology, Genetics, Genomics, Biochemistry, Bioinformatics, Computational Biology, Immunology, Neuroscience, Microbiology, or a closely related life science field.
- Hands-on research experience in an academic, institutional, or industry research laboratory.
- Professional written and spoken English (C1 or higher).
Strongly Preferred
- Wet lab experience: you have personally performed experiments (e.g., PCR/qPCR, cell culture, sequencing library prep, Western blot, protein purification, LC-MS sample prep, CRISPR workflows).
- Academic research experience: postdoctoral position, staff scientist, research faculty, or equivalent.
- Peer-reviewed publications, ideally as first or corresponding author.
- PhD from a top research university (US, UK, or other leading institutions).
The platform posted this on 15 Oct 2026.