Pharmacokinetics and Systems Biology Task Designer

As a Pharmacokinetics & Systems Biology Expert, you will play a pivotal role in developing a large-scale benchmark aimed at evaluating the capabilities of advanced AI systems in tackling complex scientific and engineering challenges. Your primary responsibility will be to design original, graduate-level computational problems that assess whether AI can effectively utilize real scientific software for research-level tasks, including running simulations, interpreting results, and designing experiments.

• Create challenging computational problems that require the use of specialized scientific software.
• Design problems that test AI''s ability to compute exact answers from defined setups and execute complex, multi-step workflows.
• Develop harder problems that necessitate strategic planning of queries or experiments to uncover hidden information.
• Conduct testing loops against state-of-the-art AI models and refine problems to achieve the desired difficulty level.

We are particularly interested in candidates with extensive, hands-on experience in:

• Pharmacokinetics & Systems Biology, utilizing tools such as libRoadRunner, Tellurium, or SBML for compartmental PK/PD modeling, enzyme kinetics, or systems biology simulations.
• Experience with other specialized software in this domain will also be considered.

• Graduate-level expertise (MS or PhD preferred) in a relevant STEM field, with practical experience using the specified tools.
• Demonstrated proficiency with at least one of the scientific software libraries, evidenced by research publications, open-source contributions, or professional work.
• Strong Python programming skills for writing problem setups, oracle functions, and solution validators.
• Ability to work independently and iteratively refine problem designs based on feedback.
• Comfortable working in a Linux/terminal environment with remote compute sandboxes.
• Availability for at least 15, 20 hours per week.

• Experience across multiple domains or tools listed.
• Familiarity with benchmark or evaluation design.
• Background in scientific teaching or exam/problem-set design.
• Experience with computational reproducibility and containerized environments.

Please be aware that this application includes a coding assessment as part of the evaluation process.