Mechanistic Modeller

Requirements

• Educated to PhD in a subject with a high mathematical content, ideally applied to a biological challenge.
• Demonstrated experience in mechanistic modelling particularly in the area of pharmacokinetics and/or physiologically based kinetic modelling.
• Proficiency with analytical and numerical methods to solve ordinary differential equations and the application of relevant software (e.g. Python and/or Matlab).
• Experience with modelling software and programming languages.
• Expert knowledge of mathematics, mechanistic modelling methodologies and data sources.
• Ability to translate complex problems into fit-for-purpose models to address them and communicate complex modelling concepts and results effectively to researchers from diverse backgrounds.
• Demonstrated ability to lead capability development activities and to deliver technical leadership.
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Benefits

Additional Information

Syngenta's Predictive Science team is looking for a Mechanistic Modeller to join our Product Safety function. Within this role you will build and apply mathematical models that predict how our compounds behave in biological systems to meet society's needs. You will coordinate and contribute to the building of mechanistic models to aid understanding and predict chemical effects in various systems (e.g. human, mammalian, environmental and/or non-target organisms) from which critical endpoints relevant for Product Safety in agrochemical research are derived. You will work at the frontier of computational science, translating complex toxicological and environmental challenges into actionable insights for cross-functional research teams. Key responsibilities will include: Liaising with project teams to understand data and modelling requirements and formulate problems in modelling terms. Coordinating and contributing to the design and development of mechanistic models, including pharmacokinetic and physiologically based kinetic (PBK) models, to evaluate chemical risk in mammalian and environmental systems. Managing and interpreting model outputs including specification, conduct, problem solving, reporting and interpretation for deployment to end users. Communicating model development, use, and limitations clearly to a wide and varied community of end users. Supporting the deployment of models for routine use. Seeking out latest developments in mathematical modelling and in consultation with senior technical experts assessing their potential use to support crop protection research. Building and maintaining scientific networks both internally and externally, delivering impactful presentations and collaborating across research teams to ensure the right modelling capability and long-term strategy.

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