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

About the role

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.

Scope of Work

• 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.

What you’ll bring

• 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).

Preferred Qualifications

• 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).

Benefits

Not provided in the source listing.

Contract & Payment Terms

• Source posting label: Today, captured 16 October 2026; approximate employer posting date 16 October 2026. The exact source timestamp and timezone were not supplied. Remolity publication is tracked separately.

Where you can work

The listing states worldwide eligibility. Confirm work authorization with the employer.

Remote does not always mean work from any country. Always check the employer’s location and working-hour requirements.