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Field
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://www.academictransfer.com/en/jobs/363733/phd-candidate-multimodal-and-ag… Requirements Specific Requirements Profile We welcome candidates with an MSc or equivalent expertise in artificial intelligence, medicine, computer or
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fundamental learning procedures to tackle distressing images related to aversive memories. The aim is to generate insights with direct impact on clinical practice and patient wellbeing. PhD Candidate Reducing
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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organisation, while MRI metabolic imaging offers a patient-scale perspective on related metabolic and invasive phenotypes. This PhD research will be carried out at the IBGC as part of the ShadowEV-GBM
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PhD in Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of
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CoE (https://www.med.uio.no/hth/english/ ) is inviting applications for a three‑year PhD position. The recruited candidate will take part in UiO Emerging Technologies Initiative Project FTI-NAM. NAM
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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written and oral English are a prerequisite. English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd
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19 Aug 2026 Job Information Organisation/Company KU LEUVEN Research Field Engineering » Electrical engineering Engineering » Electronic engineering Engineering » Computer engineering Computer
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PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis Job No.: 695949 Location: Clayton campus Employment Type: Full-time Duration: 3-year and 3-month fixed-term appointment