The Artificial Intelligence Lab in the Department of Computer Science at Vrije Universiteit Brussel (VUB) is looking for a motivated PhD researcher in Computer Science to join a new interdisciplinary project on arbovirus prevention and control in the European Union. The project is led by Prof. Pieter Libin and is embedded in a collaboration with Hasselt University and Università Campus Bio-Medico di Roma.
Project
Mosquito-borne arboviruses such as Zika (ZIKV) and Oropouche (OROV) are expected to pose increasing risks to public health in Europe. This project aims to develop a new data-driven framework to assess invasion risk and optimize mitigation and surveillance strategies in the EU. The research combines epidemiological modelling, proxy-data fitting, and reinforcement learning for public-health decision support.
As the Computer Science PhD researcher, you will lead the research on novel reinforcement learning algorithms and contribute to the joint development of the broader modelling and policy framework. Your work will focus on multi-criteria reinforcement learning, uncertainty-aware decision-making, and explainable reinforcement learning for large-scale public-health applications.
Responsibilities
You will:
- develop new multi-criteria reinforcement learning algorithms for complex decision problems;
- design methods that exploit the geographical structure of metapopulation models;
- investigate uncertainty-aware policy learning;
- develop explainable RL methods to communicate learned policies to policymakers;
- collaborate on the epidemiological model used in the project;
- contribute to the study of mitigation and surveillance strategies, including mosquito control, vaccination policies, and surveillance strategies;
- publish results in leading conferences and journals and present your work internationally.
Profile
We are looking for a candidate with:
- a Master’s degree in Computer Science, preferably with a specialization in machine learning;
- strong interest in reinforcement learning and AI method development;
- good programming and computational skills;
- enthusiasm for interdisciplinary research linking AI and public health;
- strong English communication skills.
Experience with reinforcement learning, explainable AI, probabilistic modelling, simulation, or computational epidemiology is an advantage.
Apply here.