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Field
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microscopy techniques and image analysis (confocal, multiphoton, or other advanced imaging techniques) and/or electrophysiology. Demonstrated computational knowledge, use of ImageJ, and familiarity with 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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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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degree in Computer Science, Math, Statistics or Engineering programs. Ph.D would be an asset. Knowledge of classification algorithms, vision-language models (VLM) and Hugging Face Transformers is an asset
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Faculty of Health and Medical Sciences, University of Copenhagen Cluster for Molecular Imaging at the Panum Institute, University of Copenhagen, is seeking a PhD for a project where the aim is to
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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processes that produce energy and raw materials. The Institute of Radiopharmaceutical Cancer Research develops radiotracers for imaging of cancer biomarkers and personalized therapies. In a joint effort of
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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
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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Profile: University degree (M.Sc., diploma or equivalent) in materials science, engineering sciences, or physics Experience in at least one of the methods of X-ray imaging, transmission electron microscopy