About this role
Role Overview
Design graduate-level computational science challenges that evaluate whether advanced AI systems can perform research-oriented work with real pharmacokinetics and systems biology software. You will build and refine original problems involving simulations, result interpretation, experiment design, and extracting hidden information from data.
Key Responsibilities
- Create challenging problems requiring hands-on use of specialized scientific software.
- Develop fully specified, multi-step workflows that require exact computational answers.
- Design strategic investigation tasks where the system must plan queries or experiments, interpret partial findings, and efficiently narrow possible answers.
- Test problems against advanced AI models and refine them to achieve the intended level of difficulty.
- Write Python-based problem setups, oracle functions, and solution validators.
Qualifications
- Graduate-level training in a relevant STEM field, including an MS, PhD, or equivalent research experience. An MS or PhD is preferred.
- Deep practical experience with pharmacokinetics and systems biology tools, particularly libRoadRunner, Tellurium, or SBML-based software for compartmental PK/PD modeling, enzyme kinetics, or systems biology simulation. Experience with other specialized software in this domain will also be considered.
- Demonstrated proficiency with at least one listed scientific software library through research publications, open-source contributions, or professional work.
- Strong Python programming ability and experience using these libraries to solve real research problems.
- Understanding of tool limitations, edge cases, and how to create problems that reward careful reasoning rather than surface-level pattern matching.
- Ability to work independently, incorporate feedback into problem designs, and work in Linux or terminal-based remote compute sandboxes.
Preferred Qualifications
- Experience across multiple relevant tools or domains.
- Familiarity with benchmark or evaluation design.
- Experience teaching science or creating exams and problem sets.
- Experience with computational reproducibility and containerized environments.
Work Terms
- Remote, hourly engagement.
- Availability of at least 15-20 hours per week.
Compensation
$70-$85 per hour.