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Field
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to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position As a PhD Candidate with us, you will help turn early railway
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 5 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Candidate (f/m/x) - Organelle Biology and Proteomics in
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robotic platforms, integration of optical and imaging-based feedback, and development of modeling and control strategies for operation in complex biological environments. Particular attention will be given
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31st October 2026 Languages English English English PhD Candidate in Quantifying the Benefits of Wayside Detection for Railway Infrastructure Apply for this job See advertisement This is NTNU NTNU
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be conducted through a series of clinical research studies and is closely linked to highly specialised stroke care and neurointerventional services. The PhD student will analyze and process large
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Candidate (f/m/x) in Data Science for Biomedical Imaging
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Star formation and black hole growth are two of the most important processes in galaxy evolution. Although galaxies and their central black holes operate on very different physical scales
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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 the Leiden Institute
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop