STEM Computational Scientific Software & Evaluation Design - Pharmacokinetics & Systems Biology
TLDR
Design and evaluate graduate-level PK and systems biology computational problems for AI benchmarking, using scientific software and Python to test deep numerical reasoning.
- Design graduate-level computational problems in pharmacokinetics and systems biology grounded in real scientific workflows and simulation environments.
- Develop tasks using scientific software tools such as libRoadRunner, Tellurium, and SBML-based modeling frameworks.
- Create problem setups, oracle functions, and validation logic using Python for structured AI evaluation benchmarks.
- Calibrate and iterate problem difficulty by testing against state-of-the-art AI models and refining based on performance feedback.
- Engineer multi-step reasoning challenges involving compartmental modeling, enzyme kinetics, and system dynamics analysis.
- Ensure tasks differentiate between superficial pattern matching and deep scientific reasoning.
- Advanced graduate-level education in a STEM field such as systems biology, computational biology, bioengineering, or related disciplines.
- Hands-on experience with pharmacokinetics or systems biology modeling using tools like libRoadRunner, Tellurium, SBML, or equivalent simulation frameworks.
- Strong Python programming skills, including experience building scientific workflows, simulations, or validation pipelines.
- Demonstrated ability to work with computational models in real research or production environments.
- Comfort working independently in Linux environments and remote computing or sandboxed systems.
- Strong analytical thinking with the ability to design complex, multi-step reasoning problems.
- Availability for approximately 15 to 20 hours per week.
- Competitive hourly compensation ranging from 70 to 100 USD per hour.
- Fully remote and flexible work arrangement with self-managed scheduling.
- Independent contractor engagement with weekly payments via Stripe or Wise.
- Opportunity to contribute directly to frontier AI research and evaluation benchmarks.
- Potential for ongoing project extensions based on performance and contribution quality.
- Exposure to cutting-edge scientific and AI model evaluation methodologies.
Requirements:
Benefits:
Benefits
Exposure to advanced scientific and AI evaluation methodologies
Exposure to cutting-edge scientific and AI model evaluation methodologies.
Remote-Friendly
Fully remote and flexible work arrangement with self-managed scheduling.
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- Founded
- Founded 2020
- Employees
- 11-50 employees
- Industry
- Professional Services