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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial peptides Perform and support experimental studies across the METAMIC project
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. These problems have been compounded by the emergence of Artificial Intelligence. New forms of algorithmic manipulation have been used to sow discord in democratic societies, undermine trust in politics, and erode
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sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED models. The development of these compact models will involve collaboration with several
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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, or spatial relationships of objects—and to indicate when it is unsure about its input. Key expected outcomes include the creation of monitoring algorithms that identify early signs of performance issues, and
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specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling