Remote | Computational Pharmacokinetics & Systems Biology Scientist

Remote | Computational Pharmacokinetics & Systems Biology Scientist

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.

Computational Pharmacokinetics

• Design research-level problems involving compartmental pharmacokinetic and PK/PD models
• Develop scenarios involving dosing, concentration-time behaviour, exposure, and response
• Build computational workflows requiring multi-step simulation and quantitative interpretation
• Create problems where correct solutions depend on appropriate model setup and scientific reasoning
• Identify realistic edge cases and failure modes in pharmacokinetic simulations

Systems Biology Modelling

• Develop problems involving biochemical networks, enzyme kinetics, and dynamic biological systems
• Work with mechanistic models represented through SBML-based frameworks
• Design simulation tasks involving pathway behaviour, parameter changes, and system responses
• Create scenarios requiring interpretation of complex model dynamics
• Ensure tasks reflect authentic computational systems biology research workflows

Scientific Software Workflows

• Build problems using tools such as lib RoadRunner, Tellurium, and SBML-based software
• Write and validate computational setups using specialised scientific libraries
• Test software behaviour across realistic and challenging modelling scenarios
• Incorporate tool-specific limitations, edge cases, and numerical considerations
• Evaluate whether solutions use scientific software correctly rather than relying on superficial reasoning

Simulation & Experiment Design

• Develop tasks requiring strategic selection of simulations, queries, or computational experiments
• Create problems where important information must be inferred from partial model outputs
• Design workflows requiring candidates to determine what to measure or simulate next
• Evaluate efficiency and scientific validity of alternative investigation strategies
• Build problems where careful experiment design is central to reaching the correct conclusion

Python & Computational Validation

• Write Python-based problem setups, reference calculations, oracle functions, and solution validators
• Develop reproducible computational pipelines for scientific tasks
• Verify numerical outputs and expected solution behaviour
• Diagnose discrepancies caused by implementation, modelling, or numerical issues
• Maintain reproducibility across Linux-based remote compute environments

Problem Design & Refinement

• Create original graduate-level computational problems grounded in real research practice
• Develop both exact-answer tasks and open-ended investigation workflows
• Test tasks against advanced computational systems
• Analyse model performance and refine tasks to achieve the intended difficulty
• Ensure challenge comes from scientific reasoning rather than unnecessary complexity or brute-force computation

Reference Solutions & Evaluation

• Produce authoritative reference solutions and supporting computational outputs
• Define objective criteria for correctness, completeness, and scientific validity
• Validate that tasks have well-supported expected outcomes
• Distinguish genuine domain expertise from surface-level pattern matching
• Refine evaluation criteria based on testing and reviewer feedback

Ideal Profile

• Graduate-level expertise in pharmacokinetics, pharmacology, systems biology, computational biology, bioengineering, or a closely related STEM field
• MS, PhD, or equivalent research experience preferred
• Proven hands-on proficiency with at least one relevant scientific software environment, including lib RoadRunner, Tellurium, or other SBML-based tools
• Practical experience with compartmental PK/PD modelling, enzyme kinetics, or systems biology simulations
• Strong Python programming skills
• Experience writing code for genuine research, scientific, or professional workflows
• Understanding of numerical behaviour, software limitations, and edge cases in computational modelling
• Comfortable working in Linux/terminal environments and remote compute sandboxes
• Ability to work independently and refine computational problems based on testing and feedback
• Research publications, open-source contributions, or professional work demonstrating relevant software expertise are highly valued
• Experience with benchmark design, scientific teaching, exam or problem-set development is advantageous
• Familiarity with computational reproducibility and containerised environments is advantageous

Engagement Details

• Part-time independent…