PhD and Postdoctoral Openings in Reinforcement Learning at the University of Verona

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Enrico Marchesini

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May 25, 2026, 4:51:27 AM (yesterday) May 25
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Dear all,

I am looking for a PhD student and 2+ postdocs to join a new research group at the University of Verona, Italy. The selected candidates will join a growing research environment focused on both foundational and applied aspects of reinforcement learning. The positions are fully funded through my FIS Starting Grant.

The general research focus is on trustworthy RL, with the goal of developing methods that are safe, robust, and deployable in real-world settings. Research directions include, but are not limited to:

- Cooperation and multi-agent RL
- Safety, guarantees, and verification in RL
- Reliable decision-making under uncertainty
- Applications to robotics and energy systems

We are looking for candidates with a background in RL and potentially related areas such as robotics, energy systems, control, formal methods, optimization, or machine learning more broadly.

About the group: the goal is to build a collaborative and ambitious research environment at the intersection of RL, multi-agent systems, safety, and reliable AI, with a strong focus on both theoretical foundations and real-world impact. The FIS Starting Grant also provides resources for compute infrastructure, robotics platforms, equipment, and collaborative research activities.

How to apply: if interested, please feel free to contact me directly at enrico.m...@univr.it with the subject line FISApplication2026.
📍 Location: University of Verona, Italy
📅 Application deadline: June 3 for the PhD opening - PostDocs starting dates are flexible
🔗 PhD application website: https://www.corsi.univr.it/?ent=cs&id=635&menu=iscriversi&tab=comeiscriversi&lang=en#concorsi-li-1
🔗 Postdoc applications: please send your CV and a short motivational letter by email; the positions will remain open until filled.

Please feel free to share this opportunity with students and researchers who may be interested.

Best regards,
Enrico Marchesini
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