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used to develop networks capable of self-learning and self-optimisation, adapting to real-time changes in traffic and demand. The successful candidate will contribute to designing solutions that optimise
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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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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and educational issues with the common goal of contributing to an inclusive, open and resourceful society. Your role We are looking for a doctoral candidate with a strong computational, engineering
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Design and conduct analyses linking vocal biomarkers to validated psychological scales (e.g., PAID, PHQ-9, GAD-7). Apply natural language processing (NLP) and AI techniques to large-scale audio datasets
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Background Cardiovascular disease (CVD) remains the leading cause of death worldwide and exerts a disproportionate burden on individuals living with type 1 diabetes (T1D). Despite advances in care
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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evolutionary conservation across vertebrates in terms of muscle pattern and innervation modes (1–3). The coexistence of both vulnerable and resilient muscles within the same organism provides compelling in vivo
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Luxembourg (n = 120 at each study site). At three measurement points in 6-month intervals, the study participants will report on their resources, risk factors, health and well-being with the help of interviews