PhD Position: Robot Planning and Learning at the Donders Centre for Cognition

You will (i) work on cutting-edge research problems in motion planning, reinforcement learning and task generalisation, (ii) have access to a state-of-the-art robotics lab with simulation and real-world testbeds, (iii) collaborate with experienced faculty, industry partners and international researchers, (iv) be part of an inclusive, supportive and innovative academic culture where your ideas and contributions matter, and (v) whether you aim for a future in academia, start-ups or industrial R&D, you will receive guidance tailored to both academic growth and career development.

We value creativity, curiosity and courage to challenge the norm. You will be encouraged to present your work at top conferences (like ICRA, IROS, RSS, NeurIPS), publish in high-impact journals, and engage in open science practices.

We are looking for a highly motivated and curious PhD candidate to join our team in the field of robot planning and learning. In this role, you will conduct research on enabling robots to perform a wide range of complex tasks by integrating advanced motion planning algorithms with machine learning techniques, such as reinforcement learning, imitation learning, and task generalization. You will focus on designing intelligent robotic systems that can reason about their environment, adapt to novel situations, and make decisions under uncertainty — with real-world applications in areas like agri-food, logistics, and human-robot collaboration.

You will be part of an interdisciplinary team within the Department of Artificial Intelligence at Radboud University. Your research will involve a combination of theoretical work, algorithm development, and hands-on experiments using our state-of-the-art robotics platforms. You will have the opportunity to collaborate with other academic and industry partners across Europe, contribute to high-impact publications, and present your work at leading conferences in robotics and AI.

As part of your appointment, you will also contribute to teaching and supervision within our Bachelor’s and Master’s programmes in Artificial Intelligence or related fields. This may include supporting practical lab sessions, mentoring student projects, and assisting in course delivery — typically amounting to 10–15% of your time. These responsibilities offer you valuable teaching experience and the chance to further develop your academic profile in a collaborative and inspiring educational environment.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Robot Planning and Learning at the Donders Centre for Cognition

You will (i) work on cutting-edge research problems in motion planning, reinforcement learning and task generalisation, (ii) have access to a state-of-the-art robotics lab with simulation and real-world testbeds, (iii) collaborate with experienced faculty, industry partners and international researchers, (iv) be part of an inclusive, supportive and innovative academic culture where your ideas and contributions matter, and (v) whether you aim for a future in academia, start-ups or industrial R&D, you will receive guidance tailored to both academic growth and career development.

We value creativity, curiosity and courage to challenge the norm. You will be encouraged to present your work at top conferences (like ICRA, IROS, RSS, NeurIPS), publish in high-impact journals, and engage in open science practices.

We are looking for a highly motivated and curious PhD candidate to join our team in the field of robot planning and learning. In this role, you will conduct research on enabling robots to perform a wide range of complex tasks by integrating advanced motion planning algorithms with machine learning techniques, such as reinforcement learning, imitation learning, and task generalization. You will focus on designing intelligent robotic systems that can reason about their environment, adapt to novel situations, and make decisions under uncertainty — with real-world applications in areas like agri-food, logistics, and human-robot collaboration.

You will be part of an interdisciplinary team within the Department of Artificial Intelligence at Radboud University. Your research will involve a combination of theoretical work, algorithm development, and hands-on experiments using our state-of-the-art robotics platforms. You will have the opportunity to collaborate with other academic and industry partners across Europe, contribute to high-impact publications, and present your work at leading conferences in robotics and AI.

As part of your appointment, you will also contribute to teaching and supervision within our Bachelor’s and Master’s programmes in Artificial Intelligence or related fields. This may include supporting practical lab sessions, mentoring student projects, and assisting in course delivery — typically amounting to 10–15% of your time. These responsibilities offer you valuable teaching experience and the chance to further develop your academic profile in a collaborative and inspiring educational environment.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Quality Control for Machine Learning Using Bayesian Networks and AutoML at Donders Centre for Cognition

In this PhD position you will be part of the ELSA lab on Legal, Regulatory and Policy Aspects of Clinical Decision Support Systems. This interdisciplinary lab studies the technological, ethical and legal requirements necessary for the development and use of clinical decision support systems (CDSSs), so that their use in the clinic can be subject to rigorous quality control and certification. In this position, you will work on exploring synergies between Bayesian networks and AutoML (automated machine learning) to make better data science. On the one hand, you will work on learning Bayesian networks supported by AutoML. This will allow for the development of reproducible, data-driven Bayesian-network pipelines, which should also allow for user interaction (e.g. domain knowledge). On the other hand, you will work towards making AutoML systems more interpretable by developing Bayesian network explanations, which will allow users to get insights into the pipelines evaluated by an AutoML system. This position is linked to CDSSs as the healthcare domain is envisioned as the main application area where the novel methods will be demonstrated.
You will be part of the Probabilistic Graphical Models group at the Donders Centre for Cognition and of the interdisciplinary team of researchers and PhD candidates on this consortium project. In addition to research in this domain, you will contribute to academic teaching in the AI BSc and MSc programmes, follow courses offered by the Donders Graduate School and the national research schools IPA and SIKS, and collaborate with inspiring colleagues in the international PGM research community.

Your teaching load may be up to 10% of your working time.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Quality Control for Machine Learning Using Bayesian Networks and AutoML at Donders Centre for Cognition

In this PhD position you will be part of the ELSA lab on Legal, Regulatory and Policy Aspects of Clinical Decision Support Systems. This interdisciplinary lab studies the technological, ethical and legal requirements necessary for the development and use of clinical decision support systems (CDSSs), so that their use in the clinic can be subject to rigorous quality control and certification. In this position, you will work on exploring synergies between Bayesian networks and AutoML (automated machine learning) to make better data science. On the one hand, you will work on learning Bayesian networks supported by AutoML. This will allow for the development of reproducible, data-driven Bayesian-network pipelines, which should also allow for user interaction (e.g. domain knowledge). On the other hand, you will work towards making AutoML systems more interpretable by developing Bayesian network explanations, which will allow users to get insights into the pipelines evaluated by an AutoML system. This position is linked to CDSSs as the healthcare domain is envisioned as the main application area where the novel methods will be demonstrated.
You will be part of the Probabilistic Graphical Models group at the Donders Centre for Cognition and of the interdisciplinary team of researchers and PhD candidates on this consortium project. In addition to research in this domain, you will contribute to academic teaching in the AI BSc and MSc programmes, follow courses offered by the Donders Graduate School and the national research schools IPA and SIKS, and collaborate with inspiring colleagues in the international PGM research community.

Your teaching load may be up to 10% of your working time.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Mathematics of Nonlinear Acoustics

As a PhD candidate, you will develop novel mathematical methods for the optimal control and simulation of multiphysics systems arising in Nonlinear Acoustics. The goal is to advance our rigorous understanding and computational treatment of non-linear differential equations that describe the interaction of acoustic waves with other physical phenomena, such as heat transfer and oscillating microbubbles. Multiphysics interactions of this kind underpin various cutting-edge ultrasound applications, ranging from non-invasive cancer treatments to contrast imaging and targeted drug delivery.

The research will be supervised by Dr Vanja Nikolić. Learn here more about the project in non-technical terms.

The position is part of the NWO project ‘Taming Complex Multiphysics Systems in Nonlinear Acoustics’. It includes funding for travelling to international conferences and visiting collaborators and comes with a teaching load up to 10% of your working time.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.