T2604 - Research Fellow - AI-Enhanced Pharmacometrics (Intern)
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- Lausanne
- Befristet
- Vollzeit
- QSP Data Integration: Contribute to integrating multi data source into the existing QSP platform for key ADC programs.
- AI-Driven Modelling: Create templates for virtual population construction using AI and R to characterize populations of interest.
- Simulator Development: Build virtual trial simulators using R or C++ for predicting compound efficacy and safety.
- Decision Analysis: Develop R-based data analysis templates to define "Go/No-Go" criteria based on virtual trial simulations.
- Documentation: Thoroughly document the development process and analysis workflows to ensure knowledge retention.
- Educational Background: PhD or Master’s student in Pharmacometrics, Biostatistics, Computational Biology, Mathematics, Computer Science, or Engineering.
- Core Knowledge: Understanding basic Pharmacokinetic (PK) and Pharmacodynamic (PD) concepts.
- Modeling Software: Strong proficiency in R or Python is essential. Previous exposure to Monolix, NONMEM, Matlab or SimBiology is a significant advantage. Proficiency in C++ is considered a strong plus for simulator development.
- Team Synergy: Ability to work independently on technical tasks while collaborating effectively in a team environment.
- Organization: Strong organizational skills to manage and process data from multiple ADC programs simultaneously.
- Communication: Fluency in English (both oral and written).
- Being part of a company where innovation, collaboration, and impact aren’t just values — they’re how we work every day
- Partner with teams across disciplines, at the forefront of oncology and anti-infective development
- An inclusive and respectful workplace — proud to be Equal-Pay certified
- Grow in a culture that values people, purpose, and performance
- A chance to grow, share, and shape the future of healthcare