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and implementation of parton-shower algorithms and their matching to higher-order pertubative computations in Quantum Chromodynamics. Additionally the analyses of the results in the context of the LHC
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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. For additional information, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching and administration. This means: • You are involved in a well-funded
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. The models will help interpret how different damage scenarios affect the ambient vibration signature. Both black-box and white-box damage identification algorithms will be assessed. The resulting digital twin
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elaboration of biocatalysis for synthesis. A doctoral position is available for 3-years to work with Professor Florian Hollfelder at the Biochemistry Department of Cambridge University (https
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with CamDragon Co. Ltd, a Cambridge-based SME offering engineering consultancy and STEM education
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MV-CT workflow for historical waste characterization at SCK CEN’s LNK (Laboratory of nuclear calibrations) facility. Key innovations include advanced physics-informed reconstruction algorithms and
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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graph learning models, primarily geared towards assisting combinatorial solvers for practical graph algorithm benchmarks. Please find out more here: Dr. G. Rattan Your profile You have, or will shortly
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and data-based models for describing complex materials and (re)active molecules with a focus on their interfaces. Development and implementation of new methodologies and algorithms for simulating