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research in innovative algorithms for the analysis and interpretation of medical image data to support computer-aided disease diagnostics and intervention planning. have an established track record
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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enable the development of fault-tolerant quantum computing hardware and quantum algorithms that solve life-science-relevant chemical and biological problems. Within NQCP we are currently pursuing several
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to have experience with: Phase equilibrium calculation algorithms and their integration into CO2 capture simulation Thermodynamic modeling of phase equilibrium and thermophysical properties related to CO2
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presentations at international conferences. Expectations of qualifications: PhD in Ecology, Evolutionary Biology, or a related discipline. Demonstrated expertise in ecological fieldwork, particularly in plant or
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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of precision medicine by developing innovative statistical genetics methods, implementing state-of-the-art machine learning algorithms, and integrating artificial intelligence to uncover novel biological
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the Department of Immunology and Microbiology, Faculty of Health and Medical Sciences. This role involves developing and applying advanced bioinformatics algorithms to investigate the functional diversity
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You