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Life Sciences Research Scientist (PhD): Wet Lab & Computational Biology

micro1 · Worldwide · Contract · Remote

Job Title: Life Sciences Research Scientist (PhD): Wet Lab & Computational Biology
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 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.

Required Qualifications (MUST)

• 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:

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