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Ann Nowé

Just Landed

Posted Yesterday

PhD position: Explainable, across-instance learning (MSCA Doctoral Network) Vrije Universiteit Brussel in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 30, 2026

Country flag

Country

Belgium

University

Vrije Universiteit Brussel

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Keywords

Computer Science
Mathematics
Operations Research
Industrial Engineering
Transfer Learning
Reinforcement Learning
Explainable Ai
Combinatorial Optimization
Job Scheduling
ML

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About this position

The Artificial Intelligence Lab in the Department of Computer Science at Vrije Universiteit Brussel is offering a PhD position within Confident Data-Driven Decision Support (CoRDS), a new European Doctoral Network funded under the Marie Skłodowska-Curie Actions. The project sits at the intersection of machine learning and operations research, with a strong focus on learning methods for optimization problems that must work across similar problem instances.

The research topic is explainable, across-instance learning. You will investigate how reinforcement learning, combined with structured neural networks such as graph neural networks, can improve scheduling and other combinatorial optimization problems. A central challenge is how to transfer knowledge between related instances, make learned policies robust to concept drift, and understand how these methods generalize across optimization settings.

Hosted at VUB and supervised by Prof. Ann Nowé, the position is part of a multidisciplinary, international network of doctoral candidates and supervisors. You will collaborate with the University of Vienna as an academic partner and with OMP as an industry partner, gaining exposure to both academic and applied research environments.

The role includes developing reinforcement learning methods for structured optimization, creating explainability techniques that make solution strategies understandable to practitioners, and contributing to a public benchmark based on an optimization problem from OMP. The project also involves research dissemination through leading conferences and journals, as well as participation in the network’s training and networking activities.

Overall, this is a research-intensive PhD in AI for optimization, with international collaboration and planned secondments in both academia and industry.

Funding details

Available

What's required

Applicants should have a Master’s degree in Computer Science or a related field such as Mathematics, Engineering, or Operations Research, preferably with a specialization in machine learning or optimization. A strong interest in reinforcement learning, structured neural networks, and combinatorial optimization is expected, along with good programming and computational skills, enthusiasm for research linking AI method development with industrial applications, and a strong command of English, which is the only language requirement. Experience with reinforcement learning, deep neural networks, scheduling, operations research, transfer learning, or explainable AI is an advantage.

How to apply

Apply by email before 30 Nov 2026, 18:00 Brussels time. Send your application to [email protected] and [email protected], and include a detailed motivation letter addressing the position and your experience in operations research and machine learning.

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Professors

Prof. at Vrije Universiteit Brussel

University Name
Country flag

Belgium

Research Interests

Reinforcement Learning

Transfer Learning

Ml

Computer Science

Mathematics