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Digital History (C²DH) at the University of Luxembourg is an interdisciplinary research centre committed to high-quality research and public dissemination in the field of contemporary history with a
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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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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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stacking, both high performance and (very) high density can be achieved by this concept. The mission will be to explore, understand and develop the fundamental physics of device operation. This will require
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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implement innovative solutions to enable seamless operation in connected and autonomous mobility use cases. - Validate research outcomes through a combination of high-fidelity simulations and
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a powerful model for uncovering muscle-specific protective processes. Yet, significant gaps in our knowledge have hampered advancement in this field including the lack of molecular markers and
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highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. All qualified individuals
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the organising principles of biological information processing, focusing on the underlying physics of computations and sensory environments. This exploration has led to developing models and advanced statistical