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Field
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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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metabolism and performance. Working across in vivo, ex vivo, and in vitro systems, you will integrate advanced cardiac imaging, metabolic flux analysis, and biochemical profiling to connect molecular damage
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affects the performance of plasmonic structures in photovoltaics and imaging. About this position In this position you will leverage materials with high thermal conductivities (e.g. 2D materials) to achieve
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animal stories that later morphed into the medieval Bestiary. The project employs various computational methods in intelligent imaging, text processing and metadata federation to understand how
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, drying, and curing affect adhesion, mechanics, and wear resistance. Characterize inks using advanced experimental techniques like synchrotron imaging (e.g. at the ESRF in Grenoble), DMA, nanoindentation
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to get the best possible picture of your knowledge, insight, skills, and personality. Below you can find the qualifications we consider important for the position. As a successful candidate: You have an
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instrumented building models (impervious and with openings). Experiments will use Phase-Detection Probes, high-speed imaging and force/pressure measurements to simultaneously capture detailed air-water features
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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 Join us in unravelling the complexities of the brain by cryo-EM/ET imaging
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stem cells or stem cell-based biomaterials? And eager to explore cutting-edge technologies like genome editing and in vivo imaging? Or are you perhaps fascinated by eye research and do you have an
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cells or stem cell-based biomaterials? And eager to explore cutting-edge technologies like genome editing and in vivo imaging? Or are you perhaps fascinated by eye research and do you have an affinity