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

What you'll do

This is the problem-setter side of AI training. You write challenging, expert-level life sciences questions with solutions that can be checked, then grade how AI models answer them, looking for the kind of error a non-specialist would wave through. Each problem comes with a detailed rubric and a reference answer grounded in primary literature and established experimental or computational methods.

The distinctive part is the bridge between bench and code: you assess whether a proposed experiment, an analysis pipeline or an interpretation of results is scientifically sound. The ad's subject list is broad (genomics, single-cell and spatial omics, epigenomics, proteomics and metabolomics, microbiome, structural biology, drug discovery, systems biology, clinical and translational research). Your written reasoning is peer reviewed, and quality is reached through rounds of feedback. Remote contractor work; hours are not stated.

Who fits

• A completed PhD in biology, molecular biology, genetics, genomics, biochemistry, bioinformatics, computational biology, immunology, neuroscience, microbiology or a close life science field; unlike some sibling ads, no "equivalent experience" route is offered
• Hands-on research experience in an academic, institutional or industry lab
• English at C1 or above, written and spoken

Strongly preferred

• Wet lab experience you did yourself: PCR/qPCR, cell culture, sequencing library prep, Western blot, protein purification, LC-MS sample prep or CRISPR workflows
• A postdoc, staff scientist or research faculty post, or equivalent
• Peer-reviewed papers, ideally as first or corresponding author
• A PhD from a top research university; the ad names the US and UK as examples

What it pays

micro1 lists $45–90/hour. The ad does not explain placement within the band; given how heavily it weights postdoc experience, first-author papers and institution, those are likely to matter, but that is our reading, not micro1's statement. No payment schedule is published on the listing.

Worth knowing

Good:

• The short required list (degree, lab experience, English) makes eligibility easy to self-check
• Experimentalists are the target here, not only computational people; bench skills count in your favour
• Broad topical scope, so most life science specialties have a home
• 50 openings, High demand, no country restriction

Less good:

• The "top research university" preference may count against strong candidates from elsewhere
• The listing's required-skills panel names computational chemistry tools (Gaussian, GROMACS, ORCA, Psi4 and others) that the job description never mentions; treat it as template residue and go by the description
• Peer review and iterative feedback mean early tasks can be sent back for revision
• Hours, project length and customer are not published

About this listing

Taken from micro1's referral jobs board, which we read on 18 October 2026, four days after this ad was posted. The rate, opening count, location and qualifications are micro1's own wording, summarised here; we could not verify hours, duration, or how much of the work is writing versus grading. See micro1.