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The Dutch Institute for Fundamental Energy Research (DIFFER) performs leading fundamental research on materials, processes, and systems for a global sustainable energy infrastructure. We work in close partnership with (inter)national academia and industry. Our user facilities are open to...
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Your job Do you enjoy working at the interface between behaviour, ecology, and evolution? Then you might be the PhD candidate we are looking for! In this project, you will investigate how swarming
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Faculty of Science The Faculty of Science (FNWI), part of Radboud University, engages in groundbreaking research and excellent education. In doing so, we push the boundaries of scientific knowledge and pass that knowledge on to the next generation. We seek solutions to major societal challenges,...
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Do you want to help us make AI more efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis
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Vacancies PhD Position in Algorithmic Energy Trading Key takeaways In recent years, the energy sector has undergone changes that have a high impact on the dynamics in power markets. One
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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lead to better and fairer outcomes—challenges such as cognitive overload, uncalibrated (dis)trust in AI, and unclear strategies for bias mitigation limit its effectiveness in practice. This PhD project
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community of gifted researchers, professionals or patient partners who are dedicated to making a real impact on population health and healthcare. Read what it is like to do a PhD at the Radboud University
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About the Department of ISOM The PhD position will be based in the Department of Information Systems & Operations Management (ISOM) of TISEM, a high-quality and high-impact research group of TiSEM
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unclear strategies for bias mitigation limit its effectiveness in practice. This PhD project addresses the following central research question: how can we design human-AI collaboration to mitigate biases