Advisor / Sr. Advisor – PK/PD & Pharmacometrics

About the Team 

The Global Pharmacokinetics/Pharmacodynamics and Pharmacometrics (PK/PD & PMx) Department serves as the functional leader in research and development across the value chain, from preclinical lead molecule identification through clinical post-approval. Our mission is to accelerate the development of innovative medicines by applying mechanistic reasoning and quantitative modeling to complex systems. We partner across disciplines to simplify and enable critical decisions. We are leaders in model-informed drug discovery and development. Using deep quantitative thinking, we work best with hard questions, and our insight shapes the medicines that reach patients. 

The PMx team operates across all phases of drug development and serves as a strategic scientific partner to project teams, regulatory functions, and senior leadership. We are currently investing in automation, AI/ML integration, and standardized modeling workflows to accelerate timelines and expand our impact. 

We seek dynamic, curious, and collaborative quantitative scientists ready to engage and work on life-changing therapies for patients. This role is for a scientist who wants to own the modeling and simulation on real programs and be trusted with the answer. You will develop and apply population PK and PK/PD models independently, author the analysis plans and reports behind them, and work as a scientific partner and not as an analysis service. Your work will span multiple programs within PK/PD & PMx. You will take it to project teams and department forums, and build the judgment that turns a modeling result into a development decision. 

Key Responsibilities 

Scientific and technical delivery 

• Independently develop, evaluate, and apply population PK and PK/PD models to answer defined development questions, using NONMEM and/or Monolix with R for data handling, diagnostics, and simulation. 

• Serve as PMx lead on assigned programs: primary author of the analysis plan, author of the modeling report to regulatory submission standard, and accountable owner of the analysis end to end. 

• Provide scientific input to project teams on dose, regimen, patient population, and development strategy, including dose justification, exposure-response analyses, and responses to health authority questions. 

• Perform quality control and quality review of modeling deliverables, and support scientific oversight of vendor-delivered analyses. 

• Identify where modeling can answer a question the team has not thought to ask, and say so. 

Partnership and collaboration 

• Partner with the PK/PD project leader on the quantitative strategy for your programs, starting from the scientific question and determining the best approach to answer it. 

• Build a cross-functional network across statistics, regulatory, medical, ADME, toxicology, and clinical development. Show up wherever modeling input or output is being discussed, and be engaged in those conversations. 

• Bring your work to the department forums, including scientific project reviews, and be open about what is still uncertain. 

• Elevate the people around you: share what you learn rather than holding it. 

Automation, innovation, and AI 

• Use and extend the department's automation stack in day-to-day delivery.  

• Contribute to shared tooling, templates, and standards so the next analysis starts further along than the last one. 

Communication 

• Communicate quantitative results clearly and at the level appropriate to the audience, from project teams to senior partners. 

• Share work externally over time, through scientific meetings, publications, and regulatory interactions. 

• Communicate clearly, concisely, and on time, in writing and in person. Seek feedback actively and give it constructively. 

Basic Qualifications 

• PhD in pharmacometrics, population pharmacokinetics/pharmacodynamics, computational sciences, engineering, chemistry, statistics or a related modelling area. 

• Experience in population PK and/or PK/PD modeling. Thorough understanding of pharmacokinetic and/or pharmacodynamic principles, along with an ability to clearly communicate theories and concepts to specialist and non-specialist audiences. 

• Experience using relevant software such as NONMEM (or Monolix), R, and mrgsolve. 

Additional Skills & Preferences 

• Hands-on experience across the full modeling workflow: dataset specification and creation, exploratory data analysis, covariate evaluation and modeling, model evaluation (VPC, NPDE, goodness-of-fit), simulation, and reporting. 

• Experience contributing to a regulatory submission or a health authority response. 

• Reproducible analysis practice, including version control (Git) and literate reporting such as Quarto. 

• Active engagement with AI and automation in a pharmacometrics context, including hands-on experience with tools, curiosity about what is possible, and the judgment to tell where automation helps and where scientific judgment has to stay human. We are in the middle of a transformation and this person will be part of it. 

• Comfort working when the question is not yet fully defined, and a willingness to propose the approach rather than wait to be handed one. 

• Adept at working with cross-functional colleagues. 

• Excellent self-management and organizational skills, with the ability to prioritize across several programs.