We are sharing a specialised part-time consulting opportunity for computational pharmacokinetics and systems biology professionals with strong expertise in PK/PD modelling, biological simulation, SBML-based workflows, scientific Python, and research-grade computational software.
This role focuses on designing challenging computational problems based on authentic pharmacokinetics and systems biology workflows. Selected experts will build graduate-level scientific tasks involving simulation, model interrogation, experiment design, and quantitative reasoning, then test and refine those tasks to ensure they require genuine scientific problem-solving.
Key Responsibilities
Computational Pharmacokinetics
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Design research-level problems involving compartmental pharmacokinetic and PK/PD models
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Develop scenarios involving dosing, concentration-time behaviour, exposure, and response
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Build computational workflows requiring multi-step simulation and quantitative interpretation
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Create problems where correct solutions depend on appropriate model setup and scientific reasoning
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Identify realistic edge cases and failure modes in pharmacokinetic simulations
Systems Biology Modelling
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Develop problems involving biochemical networks, enzyme kinetics, and dynamic biological systems
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Work with mechanistic models represented through SBML-based frameworks
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Design simulation tasks involving pathway behaviour, parameter changes, and system responses
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Create scenarios requiring interpretation of complex model dynamics
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Ensure tasks reflect authentic computational systems biology research workflows
Scientific Software Workflows
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Build problems using tools such as libRoadRunner, Tellurium, and SBML-based software
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Write and validate computational setups using specialised scientific libraries
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Test software behaviour across realistic and challenging modelling scenarios
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Incorporate tool-specific limitations, edge cases, and numerical considerations
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Evaluate whether solutions use scientific software correctly rather than relying on superficial reasoning
Simulation & Experiment Design
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Develop tasks requiring strategic selection of simulations, queries, or computational experiments
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Create problems where important information must be inferred from partial model outputs
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Design workflows requiring candidates to determine what to measure or simulate next
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Evaluate efficiency and scientific validity of alternative investigation strategies
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Build problems where careful experiment design is central to reaching the correct conclusion
Python & Computational Validation
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Write Python-based problem setups, reference calculations, oracle functions, and solution validators
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Develop reproducible computational pipelines for scientific tasks
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Verify numerical outputs and expected solution behaviour
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Diagnose discrepancies caused by implementation, modelling, or numerical issues
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Maintain reproducibility across Linux-based remote compute environments
Problem Design & Refinement
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Create original graduate-level computational problems grounded in real research practice
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Develop both exact-answer tasks and open-ended investigation workflows
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Test tasks against advanced computational systems
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Analyse model performance and refine tasks to achieve the intended difficulty
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Ensure challenge comes from scientific reasoning rather than unnecessary complexity or brute-force computation
Reference Solutions & Evaluation
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Produce authoritative reference solutions and supporting computational outputs
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Define objective criteria for correctness, completeness, and scientific validity
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Validate that tasks have well-supported expected outcomes
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Distinguish genuine domain expertise from surface-level pattern matching
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Refine evaluation criteria based on testing and reviewer feedback
Ideal Profile
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Graduate-level expertise in pharmacokinetics, pharmacology, systems biology, computational biology, bioengineering, or a closely related STEM field
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MS, PhD, or equivalent research experience preferred
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Proven hands-on proficiency with at least one relevant scientific software environment, including libRoadRunner, Tellurium, or other SBML-based tools
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Practical experience with compartmental PK/PD modelling, enzyme kinetics, or systems biology simulations
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Strong Python programming skills
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Experience writing code for genuine research, scientific, or professional workflows
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Understanding of numerical behaviour, software limitations, and edge cases in computational modelling
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Comfortable working in Linux/terminal environments and remote compute sandboxes
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Ability to work independently and refine computational problems based on testing and feedback
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Research publications, open-source contributions, or professional work demonstrating relevant software expertise are highly valued
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Experience with benchmark design, scientific teaching, exam or problem-set development is advantageous
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Familiarity with computational reproducibility and containerised environments is advantageous
Engagement Details
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Part-time independent contractor engagement
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Fully remote
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Minimum availability of approximately 15–20 hours per week
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Flexible scheduling based on project requirements
- Compensation: $60–$75/hour
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Work may include computational problem design, simulation development, reference-solution creation, testing, and validation
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Projects may be extended, shortened, or concluded based on project needs and performance
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
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H1-B and STEM OPT support is unavailable for this engagement
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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