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software Analyze software for new, moderately complex systems and algorithms Perform data analysis, test and debug software Develop, implement and execute plans and tests Design and apply basic data sources
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are currently seeking applications for a Postdoctoral Research Associate in all algorithmic areas of Theoretical Computer Science. In this role you will work closely with Drs Wirth, Mestre and Canonne
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combine rigorous algorithm design with applied experimentation in realistic mobile-network settings, with a strong emphasis on research excellence, publishable outcomes, and practical relevance for 6G
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models for maritime, aerial, and underwater robots. - Designing, implementing, and evaluating navigation, control, and mission planning algorithms. - Studying multi-robot coordination and human-robot
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devices.Novel decomposition algorithms will estimate motor unit activity during voluntary contractions, together with tools for robust assessment of neural markers of motor unit correlation.A control framework
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that integrate physical constraints (Physics-Informed Neural Networks), as well as for the implementation and optimization of the associated algorithms. The researcher will analyze and interpret experimental and
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Approach ( https://vhrz669.hrz.uni-marburg.de/ssf/ ). Understanding the mechanisms controlling subsurface flow (SSF) and the conditions under which it occurs remains a major challenge in hydrology and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
algorithms, data models, ontologies, and semantic data harmonization and integration strategies for a variety of translational research contexts, including the following data types: clinical research variables
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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validated algorithms. The objective is to identify sensorimotor signatures of fall risk that may improve current predictive models and contribute to the development of more targeted prevention strategies