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recruiting and selecting staff and students. You will collaborate with a team of clinicians (urologists/pathologists), experienced researchers with backgrounds in image analysis, machine learning, pathology
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Apply now Babies have so much to learn in such a short period, but how does learning itself develop? Join our research team to follow infants from 5 and 10 months to 2 ½ years to answer this pressing
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underlying health and healthcare. They collaborate with partners from all over the world to improve health outcomes for all. Radboudumc unites patient care, research, education, and corporate learning, which
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Babies have so much to learn in such a
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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Psychopharmacology at the Faculty of Psychology and Neuroscience (FPN), supervised by Dr. Ryszard Auksztulewicz and Prof. Sonja Kotz, in close collaboration with Prof. Andre Marquand at Radboud University. You will
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groundbreaking research, providing high-quality education, offering excellent support, and fostering collaborations within and outside the university. In doing so, we contribute indispensably to a healthy, free
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addresses the following central research question: how can we design human-AI collaboration to mitigate biases and foster equitable decision-making? To answer this question, the research will explore areas
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provide to infrastructure managers You will be part of a multidisciplinary project with leaders in the domain of infrastructure governance and modelling. You will learn to conduct research independently and
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European CLARIFY project and continues this research with a postdoc, PhD student and lab technician. You will closely collaborate with clinicians to define clinically relevant questions, digitize pathology