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methodologies, including machine learning, deep learning, TinyML, federated learning, explainable AI (XAI), digital twins, and other emerging techniques relevant to the RGs. Support interdisciplinary research
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, applying it to data analysis, econometric modelling, machine learning solutions, and the automation of research and data processing; Practical experience in the IT industry, developing, deploying, and
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and experimental research in the field of plasmonic nanostructures and related nanosystems, including proficiency in analytical and numerical simulations, as well as machine learning methods; work
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or multimodal physiological signal analysis; Experience applying machine-learning or advanced statistical methods to biomedical data, preferably in a physiology-informed, hypothesis-driven, or interpretable