Beschreibung
At Debiopharm, every step we take is guided by one purpose: improving the lives of people affected by cancer and infectious diseases. As a privately-owned Swiss biopharmaceutical company, we-re driven by science, but above all, by the people behind every treatment - the patients and their families.
Through our unique -development only- model, we bring forward promising therapies and transform them into treatments that can reach those who need them most, faster.
Are you ready to be at the forefront of the model-informed drug development (MIDD)? Debiopharm International SA is seeking a highly motivated Research Fellow (Intern) to help build an AI-enhanced Quantitative Systems Pharmacology (QSP) platform. This project offers a unique opportunity to integrate preclinical, clinical data and real-world data with mathematical models and AI to accelerate the development of our Antibody-Drug Conjugate (ADC) pipeline. You will work directly on assets, bridging the gap between systems biology and data-driven decision-making.
### **Research Fellow - AI-Enhanced Pharmacometrics (Intern)** ###
Location: Lausanne, Switzerland
Department: Clinical Pharmacology & Pharmacometrics
Project: 12-months internship
### Executive Summary of the Internship ###
The primary mission of this fellowship is to develop and standardize a custom QSP platform for the Debiopharm ADC pipeline. By utilizing AI and advanced modeling techniques, you will contribute to a "Digital Twin" environment to simulate virtual trials, optimize dosing regimens, and establish "Go/No-Go" criteria. This role is central to a specific project strategy, aiming to shorten development timelines and enhance our proprietary MIDD capabilities.
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### Key Responsibilities ###
* 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.
### Profile Required ###
* 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).
### What we Offer: ###
* 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
### What to Expect in the Recruitment Process: ###
If your application is selected, you-ll be invited to interviews with Talent Acquisition and the Hiring Manager via Teams, followed by a panel interview and reference checks. Communication is handled via Workable-check your spam folder for emails from \*@outbound.workable.com.
Please contact our HR Department prior to submitting any profiles. We cannot accept unsolicited applications from agencies or recruiters.