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Modelling and Simulation PK/PD Expert

Lieu Göteborg, Comté de Västra Götaland, Suède Job ID R-229644 Date de publication 06/19/2025

Are you a passionate individualwith expertise in mathematical modelling and pharmacokinetics-pharmacodynamics (PK/PD)? Do you want to contribute to 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 influence drug project teams, guiding the selection of targets, molecules, optimal dosing strategies, patient populations, and overall development pathways.

You will have the opportunity to 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 DMPKand PK/PDinnovation 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, preferably in a preclinical/translational setting

  • Industry or academic experience inexposure-response modelling(PK/PD, NLME, PBPK and/or QSP) including hands-on experience with scriptable modelling softwares (e.g., Phoenix, R, Matlab, Python, Monolix, NONMEM)

  • Demonstrated scientific leadership through a publication track record in relevant area

  • Excellent interpersonal skills and the ability to work in cross-functional teams

  • Excellent communication skills in English, both verbal and written

Desirable Skills/Experience:

  • Experience in pharmaceutical research and development

  • Experience in PBPK modelling (e.g.Simcyp or PK-Sim

  • Experience in defining quantitative modelling strategies across various therapeutic modalities (e.g., small molecules, oligonucleotides, peptides, proteins, antibodies or cell/gene therapy)

At AstraZeneca, we are driven by results and use our unique blend of science and commercial knowledge to spot opportunities and drive outcomes. We are part of an expansive healthcare ecosystem that connects key players across the entire patient journey. Our patient-first approach informs every decision we make. We are committed to your development and believe that your best is better here. Join us and be part of a global team filled with the smartest minds.

Ready to make your mark? Apply now and be a part of our journey to redefine the future of healthcare! Welcome with your application no later than July 2nd, 2025.



AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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