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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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methods for eliciting and aggregating safety specifications and risk thresh-olds for AI systems, with a particular focus on mechanisms that provide axiomatic guarantees, are algorithmically tractable, and
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understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience. To find more information
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investigate how machine-learning based algorithms can be used to personalize the user experience. The goal of this personalized user experience is to enable each individual user to discover their own
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of stroke patients and healthy volunteers. Developing algorithms for identifying and excluding motor unit filters associated to impaired motor units. Integrating real-time-decoded features of motor unit
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) and cover a wide range of innovative topics, from the development and validation of novel methods, algorithms and EO products to innovative climate research; the development of improved climate data
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space systems; Investigating and implementing PQC algorithms to safeguard space data systems against quantum computing threats; Evaluating the performance and security of PQC solutions in the context
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to pharmacy, from neurosciences to computer science, and from molecular and evolutionary biology to marine biology. Our researchers pursue fundamental key questions while collaborating with partners from
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studies independently, working with diverse datasets, developing algorithms and decision rules, and contributing to the refinement of data-driven intervention strategies. Tasks As a postdoctoral researcher
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this position will be to provide in vitro biochemical, biophysical and structural data from novel mutants of the EGFR kinase domain to drive and validate algorithmic development. Organisation The vacancy is