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/technical challenges Project FITNESS will build upon and extend state-of-the-art methods [1], [2] recently developed within the team, showing to outperform existing, machine-learning based approaches in
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technologies to enhance vehicle performance and safety, including the creation of generalised machine learning training processes. Additionally, AI-driven adaptation strategies will be investigated to enable
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transition probabilities. Use machine learning approaches to optimize model performance and run simulations over multiple time scales. Validate and improve the model with experimental data collected by
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thematic areas: Control systems, computational intelligence and machine learning, autonomous systems, optimization and networks, embedded and real-time systems hardware and software, fault diagnosis, cyber
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possible to train a machine learning model to identify tumor-reactive T cells infiltrating any tumor type, cutting months off the time it takes to develop personalized cell therapies for patients. We
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related subject (or be close to completing the degree); demonstrated interest in AI reasoning systems, algorithms, IoT, context-aware pervasive computing, machine learning and data analysis, software
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tools such as LTSpice (preferred)/TINA/Multisim. Knowledge of low-power biopotential amplifier design and energy harvesting techniques is preferred. Candidates with machine learning skills, particularly
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(www.ledbyexperience.org) and network of collaborators in a recent review stated that societal issues of climate change, military conflict, and criminality, are inevitably connected with those of mental health and well
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of structures, facilitating a form-finding process driven by FEM analysis. Training deep learning algorithms to suggest multiple structural concepts tailored to specific boundary conditions. Expanding FEM
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that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method