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starting earliest on 1st September 2024. Our research group Our research group focuses on medical imaging working at the interface of the university and university hospital. We are a balanced mixture of
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of the project is to develop a computational approach to reconstruct the structure and dynamics of a cellular process at nanometer resolution from tens of thousands of images measured in fixed cells. We will
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imaging, electrocardiogram (ECG) and electronic health record (EHR) data to improve diagnosis, management and outcomes of heart failure. About You You will have either a PhD in the relevant subject (e.g. in
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to computer vision, particularly in the context of medical imaging. Some clinical experience is desirable, including interaction with patients. This is a full-time post, and you will be offered a fixed term
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fiber photometry. -Live imaging on awake mice -Surgery (stereotaxic injections, optic fiber implantation) -Mouse behavioral testing -Data analysis/programming A 2-year postdoctoral scholar position
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the first instance Hours: Full Time (37.5 hours per week) About the role We are seeking to appoint two talented structural biologists/protein biochemists (CryoEM and/or cellular imaging) to join the Newstead
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Post-Doctoral Research Fellow to develop and apply advanced machine learning techniques to medical imaging and diagnostic applications, including Cardiac Magnetic Resonance (CMR), Echocardiography (ECHO
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Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute (HKI) | Jena, Th ringen | Germany | 16 days ago
the prospect of prolongation. Research areas: automated image processing, classical approaches, machine learning, deep learning, etc. In the research group Applied Systems Biology , a position for a postdoctoral
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, operation of in vivo chronic imaging setup including a combined two-photon and widefield fluorescence microscope, EEG recording, and behavioral monitoring. Documents experimental procedures appropriately
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machine learning have transformed our approach to inverse problems in various fields, notably in medical imaging, enabling a deeper understanding of complex data structures. However, although sophisticated