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Two Senior Innovation Coaches (specialkonsulent) for Early-stage Medical Technology Innovation Teams
people distributes across offices in Aarhus and Copenhagen who work together to pull off the intensive 10-months fellowship programme from both an administrative, practical and subject matter perspective
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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grades were distributed in the year of your graduation will be appreciated. Please note that Aarhus BSS Graduate School reserves the right to evaluate the applications on the basis of the documentation
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properties of skeletal muscle during static and dynamic contractions. The student will also participate in early-stage algorithmic work to model muscle architecture and behavior across contraction types. In
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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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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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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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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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of teaching hours per subject per calendar year, as well as any related examination work, for the past three years. Additionally, you should provide an overview of the amount of supervisions, distributed by