Computational Biology Expert

$90–120/hrrate as listed

micro1 is contracting computational biology and medicinal chemistry specialists to annotate biological datasets and evaluate AI-generated scientific reasoning for a customer project. Work is remote, asynchronous, and contract-based, with observed rates of $90–120/hr depending on credentials and assessed depth.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work involves

You will spend most of your time reading, scoring, and correcting model output that touches drug discovery and computational biology — target rationale, SAR reasoning, ADMET interpretation, sequence and structure analysis, and the kind of literature summarization where a plausible-sounding claim can be quietly wrong. Alongside evaluation, you'll write original problem sets and case studies drawn from real medicinal chemistry challenges, then defend your reference answers when another expert disagrees. Annotation tasks lean toward complex biological datasets where the judgment call is which interpretation is defensible, not simply whether a label is right.

A meaningful part of the job is written justification. Ratings without reasoning are close to useless to the customer, so expect to explain in a few clear sentences why a model's proposed scaffold modification is chemically naive, or why its stated mechanism conflates two pathways. Contributors also help refine rubrics and curation guidelines as the project evolves.

What the platform screens for

micro1 runs an AI-led interview before any project assignment. It probes credential specifics (degree, institution, thesis area, publications), then follows up on your stated specialty with successively narrower technical questions — vague or padded answers surface quickly. Screens also test evaluation judgment: whether you can separate an answer that is wrong from one that is merely unconventional, and whether you flag uncertainty instead of guessing. No prior AI or ML experience is required.

Logistics

Fully remote, contractor engagement, asynchronous collaboration with other domain experts
Flexible scheduling; most contributors commit 10–20 hours weekly, with some projects supporting more
Pay band of $90–120/hr reflects rates observed on this listing and is not guaranteed for any individual engagement
Project duration varies with customer demand; work often arrives in batches with defined turnaround windows

What they look for

medicinal chemistry

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you hold a PhD, PharmD, or MSc in computational biology, medicinal chemistry, bioinformatics, chemistry, or a closely related field?
Advanced degree in computational biology or related field · required
Have you applied computational methods to a medicinal chemistry, drug discovery, or drug design project in an academic, industry, or research context?
Medicinal chemistry or drug discovery experience · required
Have you used bioinformatics or cheminformatics software (e.g., MOE, Schrodinger, PyMOL, RDKit, ChemAxon, or similar platforms) as part of your professional or research work?
Bioinformatics or cheminformatics tool proficiency · preferred
Do you regularly read and evaluate primary scientific literature in medicinal chemistry or computational biology to inform your work?
Primary literature engagement · preferred
Have you worked as a remote contractor, consultant, or researcher in an asynchronous role?
Remote work experience · preferred

0 of 5 answered

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Whether you have hands-on experience translating computational approaches into real chemistry outcomes, not just theoretical knowledge of tools.
A strong answer: Describe a concrete project (target selection, lead optimization, ADMET prediction, or similar), the computational methods you chose and why, what the results showed, and how they informed or changed the next step in the project.
Where people lose it: Listing tools or methods you've learned without explaining a real problem they solved, or staying so abstract that the interviewer can't verify you've actually done medicinal chemistry, not just read about it.