Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD)

$45–90/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: Sciences

Create expert scientific problems, reference answers, and grading rubrics for AI systems working across computational chemistry, structural biology, and drug discovery. Review model outputs for methodological flaws, unsupported conclusions, and subtle scientific errors.

The work

This remote, worldwide contractor role focuses on producing scientifically verifiable training and evaluation material for AI systems. Day to day, you may design difficult problems, write literature-grounded reference answers, build scoring rubrics, and assess model responses across molecular simulation, protein structure prediction and design, docking, virtual screening, QSAR/ADMET, proteomics, or metabolomics. Work is revised through feedback and peer review cycles.

What the screening is likely to test

The platform will look for a relevant PhD, hands-on academic or industry research, and professional written and spoken English at C1 or higher. Expect follow-up on methods you have personally used, including study design, validation, uncertainty, and failure modes. Python is required in practice. R and Bash are preferred additions, alongside experience with scientific writing, benchmarking, model evaluation, or molecular machine learning.

Practical details

The contract is remote and open worldwide. The listing does not state whether scheduling is fully asynchronous, how many hours are typically available, or whether there is a minimum weekly commitment, so candidates should confirm these points during onboarding.

Pay band: $45–90/hr

What they look for

Computational Chemistry
Structural Bioinformatics
Cheminformatics
Proteomics & Metabolomics
Documentation
Verbal communication
Drug Discovery
Biology
Metagenomics

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: This tests whether your claimed expertise is tied to a verifiable project, identifiable methods, and personal scientific responsibility rather than broad familiarity with a field.
A strong answer: Anchor the answer in a specific academic or industry project, stating the biological question, your own role, methods used, validation strategy, and resulting publication, dataset, or decision. Distinguish clearly between work you performed and work done by collaborators.
Where people lose it: Candidates lose points by listing tools and research areas without identifying a concrete study, personal contribution, or scientific outcome.

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