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cultures—a powerful 3D ex vivo model—this project will dissect the mechanistic links between mTOR signalling, reactive glial phenotypes, and complement activation. The project will also incorporate human
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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voiding behavior in mice and developed live imaging techniques to visualize sensory signaling in the bladder wall and dorsal root ganglion (DRG) neurons. In addition, we explore these pathways in human
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, governed by complex neural circuits. As the bladder fills, sensory signals originating from its wall inform the central nervous system about bladder fullness. Disruption of these signaling pathways can
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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of biomechanics, biomedical imaging, and neuromuscular physiology in an interdisciplinary and international environment. Limited teaching within biomechanical engineering can be expected, but also in other study
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, sports, food safety, and environmental monitoring. By integrating electrochemical techniques and imaging technologies, the unit delivers cutting-edge solutions with real-world impact. Led by Prof. María
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degree in biomedical sciences or related life science discipline We are looking for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and
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project to study tissue-resident macrophages in neurological disorders. This collaborative doctoral project is embedded within the Faculty of Pharmaceutical, Biomedical and Veterinary Sciences
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop