Counterfactual Simulation and Synthetic Data Generation for Next-Generation Clinical Trials

The project will be supervised by KU Leuven professor Maarten De Vos (Department of Electrical Engineering (ESAT) and is in collaboration with European project partners. The successful candidate will closely collaborate with other PhD candidates working on the same project and on related projects. The research is embedded in a stimulating interdisciplinary environment with state-of-the-art analysis expertise and with ample opportunities for interaction with clinicians and AI experts.

Who are we? The STADIUS-BIOMED research group at the Department of Electrical Engineering (ESAT) of KU Leuven is one of the world-leading groups developing and validating AI approaches in Healthcare, with applications covering various clinical disciplines.

The group is a friendly, close-knit collaborative team focused on delivering novel innovations into healthcare practice.

We closely collaborate with medical colleagues in UZ Leuven and with various industry partners, and have prior expertise in deploying methodology in clinical applications.

(https://scholar.google.com/citations?hl=nl&user=xTjDXdQAAAAJ)

Project

The project is part of GENz-trials. GENz-trials is a collaborative initiative aimed at transforming clinical trial design and evaluation through advanced data science, automation, and simulation technologies. Central to this project is the development of synthetic control methodologies and digital twins for informing trial protocols and emulating randomized controlled trials using retrospective and prospective data. KU Leuven leads WP5, which integrates advanced causal inference, robust counterfactual simulation, and protocol optimization analytics. Key tasks include developing emulation engines, establishing regulatory-grade validation pipelines, and benchmarking synthetic cohorts against observed results from real clinical trials

Profile

The Requirements For The Position Are

• Obtained a first class Master in a relevant field, e.g. computer science, biomedical engineering or mathematical engineering
• Good understanding of statistics and machine/deep learning algorithms
• Interest in Biomedical data science
• Excellent programming skills in Python
• Proficient English, both oral and written
• Enthusiasm about research and medical applications of AI
• Aptitude to work independently, think critically, lead project deliverables and meet deadlines
• Good team spirit, be pro-active and participate in the lab's scientific life
• Aptitutde to collaborate with local and international project partners (including technical and clinical collaborators)
  
  

Offer

We Offer

• A PhD position
• Research experience within a prestigious university (most innovative university in Europe)
• Cutting-edge research in AI for healthcare in one of the most dynamic research groups in Europe
• An international research environment by joining a multi-cultural team representing all continents
• Opportunities to collaborate with international and inter-disciplinary collaborators as part of the European projects
• Travelling opportunities to scientific events, project meetings and international stays
• Freedom to independently conduct research and contribute with own ideas
• Flexible working hours, with possibility to telework
• Competitive salary
  
  

Application Requirements

• Curriculum vitae
• Motivation letter
• Academic records (grades) for Bachelor and Master degrees
  
  

Interested?

For more information please contact Prof. dr. Maarten De Vos, tel.: +32 16 37 39 97, mail: [email protected].

You can apply for this job no later than November 30, 2025 via the online application tool

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

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