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Field
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100%, starting January 2026 (negotiable) Proteins must fold correctly to function, and this process is tightly regulated by a network of chaperone proteins. At the heart of this network is Hsp90, a
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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, we are looking forward to your scientific support at the Clinic for Radiology! We are seeking a highly motivated PhD student to join our interdisciplinary research team working on multimodal imaging
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accessible AI and XR technologies for people with disabilities through inclusive Human-Computer Interaction (HCI) and participatory design methods. Your job Around 25% of the Dutch population lives with long
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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diagnostics (theranostics), focused ultrasound (FUS), and molecular imaging (PET/SPECT). The PhD candidate will be responsible for conducting preclinical studies using animal models of glioblastoma, including
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and/or atom probe tomography Experience in image processing Experience in programming with Python or Matlab is strongly desired Team spirit as well as excellent communication and organizational skills
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or directly inside the cell. This approach requires biochemistry or cell biology for the sample preparation and scripting skills for the ET data processing. For more information, please read PMID33762348
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Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission