Modelling and Simulation PK/PD Expert

Are you a passionate individual with expertise in mathematical modelling and pharmacokinetics/pharmacodynamics (PK/PD)? Do you want to apply quantitative approaches to help shape the development of future treatments for cardiovascular, renal and metabolic diseases?

If so, we invite you to join our Modelling & Simulation team within the Early Cardiovascular, Renal and Metabolism (CVRM) therapeutic area at AstraZeneca. This position is based at our dynamic R&D site in Gothenburg, Sweden.

Accountabilities

As a Modelling and Simulation PK/PD expert, you will play a key role in shaping project strategies and driving critical decisions across our drug discovery portfolio. You will actively contribute to drug project teams, providing quantitative insights to inform target and molecule selection, dosing strategies, and translational development decisions.

You will design and oversee the execution of complex studies in preclinical disease models, applying advanced mathematical modelling approaches to deliver impactful PK/PD and translational insights. Your expertise will enable you to synthesize data from multiple sources, predict human pharmacokinetics and pharmacodynamics, and influence the definition of efficacious exposure and dosing regimens.

In this role, you will present and defend your quantitative assessments and recommendations to internal governance and senior stakeholders, shaping critical decisions at the highest levels. You will also provide scientific leadership by initiating and leading strategic DMPK and PK/PD innovation projects, fostering collaboration across disciplines, and representing AstraZeneca's modelling expertise both internally and within the broader scientific community.

Essential Skills/Experience

• PhD in pharmacokinetics, pharmacology, mathematics, or related field, with a focus on model-based PK/PD approaches.
• Industry or academic experience in exposure-response modelling such as PK/PD, NLME, PBPK and/or QSP, with hands-on experience using relevant modelling and programming tools (e.g., Phoenix, R, MATLAB, Python, Monolix, NONMEM)
• Demonstrated ability to integrate complex data, apply quantitative reasoning, and translate modelling results into recommendations that inform project decisions
• Demonstrated scientific leadership and a strong track record of scientific contributions in a relevant area
• Experience applying AI and machine learning to quantitative research workflows, for example in data curation, PK/PD modelling or translational modelling
• Excellent communication and influencing skills, with the ability to present complex quantitative results clearly to cross-functional teams and senior stakeholders

Desirable Skills/Experience

• Experience applying PK/PD modelling in a preclinical or translational setting