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into host cells. They play a central role in the spread of antimicrobial resistance and in numerous pathogenic processes. This doctoral project aims to elucidate the molecular mechanisms of substrate
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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detection and multi-animal tracking in complex environments. Behavioral analysis and animal posture recognition. Image processing under uncontrolled conditions (variable lighting, occlusions, movement
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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integrate metabolic signals, establish cellular memory, and regulate plasticity. We use cutting-edge methods (multi-omics, single cell, live cell imaging, modelling, chromatin biochemistry as well as various
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that paradigm and explores negative ion mode LC-MS/MS to reveal new molecular insights and enable broader biological discovery This PhD position is part of a vibrant research environment involving other
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and adapted tools for the processing of signals or images acquired with biomedical sensor networks (cardiology, neurosciences) or in geosciences (seismology and marine ecology), but also in wireless
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potential application in the development of contrast agents for Magnetic Resonance Imaging (MRI) and radiopharmaceuticals for diagnostic purposes. Center: Interdisciplinary Center of Chemistry and Biology
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protocols, ITC will focus on the monitoring and response parts, building on many earlier projects revolving around the use of UAV/drones, computer vision and machine learning, change and damage detection, and
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Interaction (HCI), Artificial Intelligence (AI), robotics, and accessibility, with a focus on inclusive co-creation methodologies for children with autism and eating behavior challenges. Information We invite