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Field
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Simulation Group at ICN2 conducts cutting-edge research in computational materials science, focusing on electronic structure methods, atomistic simulations, and multiscale modelling. The group develops and
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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the brain–body axis. The project will extend ongoing research by considering population diversity and heterogeneity in exposure profiles and biological responses. You will apply statistical modelling
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, and knowledge integration Safe, transparent, and privacy-preserving agent-based AI Eligibility and requirements The candidate should have a first or upper second-class BEng and MEng (or equivalent
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market using data available on online recruiting platforms, deploying state-of-the-art approaches in Natural Language Processing, Semantic Web, and Agent-based Modeling. For this purpose, an extensive
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market using data available on online recruiting platforms, deploying state-of-the-art approaches in Natural Language Processing, Semantic Web, and Agent-based Modeling. For this purpose, an extensive
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on reinforcement learning (RL) for policy discovery in a multi-sector “integrated modeling environment” that connects fast ML metamodels of simulators (e.g., transport, energy, environment, climate events). The aim
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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/embedding-based models, prompting vs. fine-tuning. Practical experience with fine-tuning and evaluation of modern language models for annotation (e.g., Adapter/LoRA, weak supervision, distillation), including