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integrated onto drone platforms engineered by project partners, with the objective of assessing the structural integrity of concrete façades. Objectives The objective of this PhD thesis is to develop a Machine
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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Hands-on lab experience and/or interest Knowledge on Machine Learning, or other AI techniques Personal Skills: Team Worker Initiative in Research and Innovation Flexibility Results-oriented Analytical and
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identification Experience in collaborative and international projects Experience/knowledge in HIL systems Hands-on lab experience and/or interest Knowledge on Machine Learning, or other AI techniques Personal
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advanced analytical and statistical techniques to extract actionable insights from complex datasets. Train, evaluate, and continuously refine deep learning and machine learning models, prioritising
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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, computational neuroscience, bioinformatics, robotics, or a related field Strong expertise in computational data analysis (e.g., behavioral analysis, signal processing, or machine learning) Experience working with
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research oriented towards applications of quantum computing, quantum algorithms, or machine learning. Publishing articles in top-tier journals and disseminating results on thematic conferences. Applying