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, including image acquisition, processing, analysis, and interpretation Develop and validate new imaging techniques, algorithms, or software to improve diagnostic accuracy and patient outcomes Collaborate with
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About the FSTM The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine
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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological
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Master/engineer degree in computer science, applied mathematics, data science with background in image processing, imaging inverse problems, deep learning and optimisation. Good coding skills for numerical
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laboratory and collaborative meetings. Collaborate actively with scientists performing wet bench experiments (PhD, postdocs). Interact productively with other bioinformatic engineers or researchers on Institut
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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. Collaborate with people with diabetes, diabetologists, software engineers, and clinical psychologists to develop and validate prototype tools. Contribute to qualitative and mixed-methods research to ensure user
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Professor in Medical Imaging. The Faculty of Science, Technology, and Medicine at the University of Luxembourg strives for excellence in the education and research of medicine, biomedical sciences and allied
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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procedure. In this context, the proposed PhD project aims to develop an innovative strategy to evaluate the efficiency and quality of surgical care. This strategy is based on data science, combining