Drug Discovery Specialist, Pharmacology & ADME/Tox

$70–100/hr

rate as listed

Workload: 20+ hrs/week
Engagement: Project-based
Location: UK, US
Field: Sciences

Evaluate and improve AI-generated work across pharmacology, DMPK, ADME/Tox and PK/PD using hands-on drug discovery experience. The role includes designing benchmark problems, reviewing scientific reasoning and defining quality standards for training data.

The work

You will create challenging drug discovery tasks and reference solutions involving assay interpretation, mechanism of action, compound liabilities and optimization strategy. Day to day, you may review in vitro ADME or safety data, PK/PD studies, CRO readouts or LC-MS bioanalysis, then assess whether an AI model reaches a scientifically defensible conclusion.

What the platform screens for

The screen is likely to focus on specific examples from early-to-mid stage discovery, including the data you examined, limitations you identified and compound decisions you supported. You should also be prepared to critique step-by-step model reasoning, distinguish factual errors from judgment calls, and explain how you would build grading rubrics or verification processes. Familiarity with PK/PD or data analysis software and scientific AI tools is expected, but coding is not required.

Practical details

This is a part-time engagement through Cincinnatus LLC, or an appropriate international entity, with potential placement in a leading AI lab's extended workforce. Candidates must be able to work at least 20 hours per week during weekdays. The listing does not specify whether the engagement is remote, fully asynchronous or tied to particular working hours beyond that weekday requirement.

Pay band: $70–100/hr

What they look for

Early-to-mid stage drug discovery experience in pharmacology, DMPK, ADME or toxicology
Hands-on interpretation of experimental drug discovery data
Scientific evaluation of assay quality, compound liabilities and PK/PD evidence
Use of PK/PD or data analysis software and scientific AI tools
Design of technical tasks, reference solutions and grading criteria
Clear written explanation of complex scientific decisions

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 you can substantiate your background with a defined target, modality, development stage, data package and decision rather than discussing drug discovery only at a conceptual level.
A strong answer: Choose one program and identify your responsibility, the assays or datasets you personally analyzed, the competing interpretations and the resulting decision. Separate your own contribution from the work of the broader team.
Where people lose it: Candidates lose points by describing a program's overall success without identifying what they personally evaluated or how their analysis changed compound progression.

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