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-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development
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assays across multiple zebrafish models of leukodystrophy. Characterise disease phenotypes using multimodal imaging and complementary experimental approaches. Apply advanced imaging techniques, including
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households or companies. But energy data is not like images or text: it consists of time series living on a physical network, governed by power-flow equations. Off-the-shelf generative models produce data
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You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic
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machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
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-agent" that integrates multimodal health data, including MRI examinations, PSMA PET/CT imaging, histopathology results, and longitudinal electronic health records, to support clinical decision-making in
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accurate despite the large temperature gradients present in cryogenic experiments. You will explore full-field techniques such as digital image correlation, speckle and grid methods, interferometry, digital
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You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic
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fundamental learning procedures to tackle distressing images related to aversive memories. The aim is to generate insights with direct impact on clinical practice and patient wellbeing. PhD Candidate Reducing
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Description Do you wish to join the new Marie Sklodowska-Curie Action Doctoral Network PREFERENCE and help us make a transformative difference in the field of molecular imaging? Then, apply to join the