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Postdoctoral Researcher in Reinforcement Learning for Epidemic Mitigation – Vrije Universiteit Brussel (VUB), Belgium

Postdoc position

8/12/2026

Vrije Universiteit Brussel (VUB) is recruiting a Postdoctoral Researcher in Reinforcement Learning (RL) for Epidemic Mitigation. The position is based at the Artificial Intelligence Lab Brussels, within the Federated Labs AI and Robotics research group, and focuses on developing reinforcement learning methods for public health decision-making in the context of epidemic emergencies.

This is a unique opportunity to work at the interface of AI, reinforcement learning, and computational epidemiology, with potential impact on public health policy and society.

Position Snapshot

  • Institution: Vrije Universiteit Brussel (VUB), Faculty of Sciences and Bioengineering Sciences, Department of Computer Science, Federated Labs AI and Robotics

  • Location: Brussels Humanities, Sciences & Engineering Campus (Elsene/Ixelles), Brussels, Belgium

  • Level: Postdoctoral Researcher (1.0 FTE)

  • Research areas:

    • Reinforcement learning for epidemic mitigation and public health decision-making

    • Multi-objective, hierarchical, explainable, and uncertainty-aware RL

    • Computational epidemiology and epidemic simulation models

  • Contract: Full-time employment (1 FTE) for 12 months, extendable upon positive evaluation of research activities

  • Planned start date: 1 October 2026

  • Application deadline: 30 September 2026

  • Application portal: VUB jobs portal – https://jobs.vub.be/job/Elsene-Postdoctoral-Researcher-in-Reinforcement-Learning-for-Epidemic-Mitigation/1415388733/

  • Contact for job content: Dr. Pieter Libin – pieter.libin@vub.be, +32 473 84 49 93


About the Research Project

The postdoc will work on reinforcement learning methods for public health decision-making in the context of epidemic emergencies. The overarching goal is to design and evaluate learning-based approaches for controlling the spread of infectious diseases under realistic epidemiological, operational, and societal constraints.

Key project features:

  • Work at the interface of reinforcement learning and computational epidemiology.

  • Develop new RL algorithms tailored to epidemic control, focusing on multi-objective, hierarchical, explainable, and uncertainty-aware decision-making.

  • Consider several types of epidemic models, including spatial models and individual-based (agent-based) models.

  • Aim to produce policies that are robust, interpretable, and relevant for epidemic preparedness and response.

The project complements ongoing research at the VUB AI Lab on epidemic decision-making and multi-objective RL for public health, and will involve collaboration with other researchers working on epidemic mitigation.

Core Responsibilities

As a Postdoctoral Researcher, you will:

  • Develop and implement reinforcement learning approaches for epidemic mitigation, with a focus on multi-objective, hierarchical, explainable, and uncertainty-aware RL.

  • Work with epidemic simulation models and formulate control problems as sequential decision-making tasks.

  • Evaluate RL algorithms under realistic constraints (e.g., healthcare capacity, compliance, economic impact, fairness) using spatial and individual-based epidemic models.

  • Contribute to scientific publications, open-source software, and reproducible research workflows.

  • Present research findings at project meetings, workshops, and international conferences.

The main focus of this position is research; teaching duties, if any, are minimal and negotiated within the group.

Required Qualifications


Academic Background

  • PhD in machine learning, artificial intelligence, computer science, applied mathematics, or a related field, awarded by the start date of the position.


Technical Skills and Experience

  • Experience with reinforcement learning, sequential decision-making, or closely related machine learning methods.

  • Strong programming skills, preferably in Python. Experience with JAX is a plus.

  • Experience with simulation-based or quantitative research (e.g., working with complex models, large-scale experiments, or numerical analysis).


Personal Skills

  • Ability to work independently as well as collaboratively in a multidisciplinary team.

  • Strong written and oral communication skills in English.

  • For non-EEA nationals: ability to meet the conditions for obtaining a valid permit for VUB and comply with VUB residence requirements.


What VUB Offers

  • A full-time employment contract (1 FTE) for 12 months, with the possibility of extension depending on positive evaluation of research activities and project funding.

  • Salary linked to one of the scales set by the government, commensurate with experience and qualifications.

  • A stimulating, international research environment within the VUB Artificial Intelligence Lab, one of the oldest AI labs in Europe.

  • Opportunities to collaborate with researchers in AI, epidemiology, public health, and related fields.

  • Access to computing resources and support for attending conferences and workshops, depending on project budget.


Application Materials

Applications must be submitted online via the VUB jobs portal. Applications sent by email will not be considered as official submissions.

Required documents:

  • Curriculum Vitae (CV) – including education, research experience, publications, and other relevant information.

  • Motivation letter – explaining your interest in the position, how your background fits the project, and your research vision.

  • Contact information for references – names and email addresses (and optionally phone numbers) of referees.

  • Up to three representative publications or preprints – demonstrating your expertise in reinforcement learning, machine learning, or related fields.

  • Links to relevant code repositories or software projects (e.g., GitHub, GitLab) – strongly encouraged if you have open-source contributions.

  • Diploma(s) – copies of your PhD degree (not applicable for VUB alumni).

Ensure that all documents are in English (or accompanied by an English summary where appropriate).

How to Apply (Step-by-Step)

  1. Read the official job posting

  2. Prepare your application documents

    • Update your CV and collect up to three representative publications or preprints.

    • Write a targeted motivation letter explaining your fit for epidemic mitigation and RL.

    • Prepare contact details for your referees.

    • Collect or generate links to your code repositories (if available).

  3. Submit via the VUB jobs portal

    • Go to the application section on the job page.

    • Fill in the online form and upload all required documents.

    • Double-check that everything is complete and legible before submission.

  4. Submit before the deadline

    • Ensure your application is submitted no later than 30 September 2026.

    • Late applications are not accepted.

  5. Follow up

    • Shortlisted candidates will be invited for an interview.

    • For questions about the job content, you can contact Pieter Libin at pieter.libin@vub.be or +32 473 84 49 93.


Selection Process

According to the official posting, the selection process is:

  1. Initial selection based on the application file (CV, motivation letter, publications, etc.).

  2. Job interview with the selection committee (may be online or on-site).

After the interviews, the committee will rank candidates and extend an offer to the top-ranked applicant.

Why This Opportunity Stands Out

This postdoctoral position offers a rare combination of:

  • High-impact research at the intersection of reinforcement learning and public health, with the potential to inform epidemic preparedness and response.

  • A focus on advanced RL topics – including multi-objective, hierarchical, explainable, and uncertainty-aware reinforcement learning – grounded in real-world epidemic control problems.

  • A collaborative, international environment in the VUB Artificial Intelligence Lab, with strong expertise in RL and epidemic decision-making.

  • A full-time contract with government-linked salary scales in Brussels, a vibrant, multicultural city hosting EU institutions and numerous research organizations.


For candidates passionate about reinforcement learning, AI for social good, and public health, this is an outstanding opportunity to pursue cutting-edge research with real-world relevance at Vrije Universiteit Brussel.

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