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are prevalent in both type 1 and type 2 diabetes and are associated with poor glycemic control and increased risk of complications. The Deep Digital Phenotyping (DDP) Lab is pioneering a new generation of digital
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to making a difference in patients' lives. Automation & Process Optimization Automation & Process Optimization Department is part of the Digital Science and Innovation (DSI) area, which supports the digital
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techniques (e.g. electron microscopy) will then be applied to assess the extent of material degradation in each case. Characterisation could include in-situ tensile testing coupled with digital image
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paper and grant writing, and thesis and viva preparation. Interviews are likely to be online in mid-late August 2025. Project Description: Deepfakes, i.e., realistic AI-generated images, videos or audio
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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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about our proposed methodology. In this method, the images taken by each drone will be loaded into the pre-processing unit and then the pre-processed data will be used as the input of the deep learning
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sustainable materials, (d) Artificial Intelligence (AI) models to predict and control the manufacturing process and (e) a Digital Twin (DT) incl. Building Information Modeling (BIM) information backbone