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Field
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You will work in an interdisciplinary team at Radboudumc, consisting of the Department of Nephrology and the Computational Pathology Group (CPG ) within the Department of Pathology . The Department
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We are seeking a highly motivated PhD candidate to join a project focused on developing a clinically compliant wireless platform for navigated capsule endoscopy and lesion detection. The research will investigate novel strategies for magnetic navigation, real-time localization, and robotic...
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Kidney transplantation is the preferred treatment for patients suffering
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Come join QuTech and create the Quantum Future! Job description Are you interested in experimental quantum optics and information science? Would you like to work on groundbreaking physics
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PhD Student Brain multiregion singlecell transcriptomics of Myalgic Encephalomyelitis/CFSyndrome NIN
) Country Netherlands Application Deadline 4 Oct 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not
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benchmark for designing circular chains and networks. The PhD position is embedded in the research programme OPERA of FEB’s Research Institute. The project will be supervised by Prof. Dirk Pieter van Donk and
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with the following qualifications, knowledge, and skills: A master’s degree (or equivalent) in computer science, human-computer interaction, traffic engineering, or related fields. A solid background and
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degree in Computer Science, Artificial Intelligence, Data Science, or a closely related discipline; Interests: You should have a strong interest in deep learning and information retrieval. (This point is
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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 Do you want to contribute to research
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Infomatter group at AMOLF. The SMIP project aims at revolutionising computing by developing adaptive, smart materials that combine memory and learning directly within their structure, uniting theory and