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The department of clinical pharmacology, modeling and simulation seeks a motivated, and mathematical modeler/ quantitative scientist / applied mathematician or statistician who will drive the development and execution of computational modeling and simulation strategies to enable next‑generation pharmacometric analyses. We are seeking a subject matter expert with experience in quantitative approaches to inform drug development. Proficiency in one or more of the following areas is highly desirable: applied mathematics, multivariate statistical methods, AI/ML-based modeling and analytics, data warehousing, automation of complex data workflows, data engineering and emerging computing technologies. Knowledge of pharmacokinetic/pharmacodynamic (PK/PD) modeling will be useful. In this role, the Principal Scientist will contribute across a broad range of activities, including, curation and visualization of complex datasets, developing and industrializing novel computational methods for QSP and PK/PD modeling and automation of pharmacometric workflows. The candidate is also expected to establish, lead and mentor a team of junior scientists to deliver on department objectives. This role is ideal for a scientific leader with quantitative science/applied mathematicsbackground and interest in PK/PD and exposure–response modeling, who is passionate about integrating quantitative methods, data science, and emerging technologies to influence critical development and regulatory decisions at a global level.
Job Responsibility
Independently developing and implementing analytics workflows to manage and analyse large, complex datasets from diverse sources, including real‑world data.
Driving innovation through the application of modern data architecture, data science engineering, data modeling, and advanced computing methodologies.
Planning and executing PK/PD analyses that integrate pharmacokinetics, pharmacodynamics, patient characteristics, and disease biology to optimize dose selection, dosing regimens, and study designs.
Mentoring and managing junior scientific staff to support modeling and simulation activities and collaborating closely with other modelers to implement data and modeling workflows for innovative pharmacometric projects.
Collaborating with cross‑functional partners, including observational research, health economics and outcomes research, statistics, and clinical biostatistics teams, to enable platform‑level analytics and modeling workflows.
Providing scientific thought leadership, guidance, and strategic input, and contributing to the external scientific community through publications and conference presentations.
Requirements
Doctorate degree and 8 years of clinical pharmacology experience OR Master’s degree and 12 years of clinical pharmacology experience
Degree in Statistical and Data sciences, Computer Science, Pharmaceutical Sciences, Engineering, or related fields with equivalent professional degrees (e.g. MD, PharmD), and experience in the life sciences, Biotechnology and/or Pharmaceutical Industry, consulting or post-doctoral training
Demonstrated experience with scripting and implementing computational algorithms, optimization and model qualification methods, data analytics algorithms and models.
Hands on experience using a modeling software (e.g. Python, MATLAB, R, Julia, NONMEM, SAS, S-Plus, SQL, etc).
Excellent interpersonal, technical, and communication skills to lead cross-functional teams
Previous record of scientific contributions through peer-reviewed articles and external presentations
Experience in PK/PD modeling and population-based analyses/simulations with established track-record of model-based drug development in multiple therapeutic areas will be an advantage