412 algorithm-development-"Multiple"-"Prof" "NTNU Norwegian University of Science and Technology" positions in Netherlands
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algorithms from medical records, improving Astronaut’s medical monitoring during missions and throughout their career; Develop automated workflow for data extraction and import; Support development
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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-centred artificial intelligence. Demonstrated experience in prototype development and with quantitative and qualitative research methods, preferably also experience with user-centred design. Interest in
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; Associated processing, mitigation, retrieval, correction and calibration algorithms for product generation. For remote sensing this includes algorithmic developments relevant to Lvl1 and Lvl2 ground processing
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operating (Waterstromen) membrane-based wastewater treatment plants. As part of the UT team, you will develop a robust model predictive control (MPC) algorithm based on sensor and other system inputs that can
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Automation group will develop novel machine-learning based control algorithms that allow for real-time adjustment of OSA therapy. The main challenge is to develop robust machine learning algorithm which can
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through ESA contracts; implementing campaigns in support of radar mission algorithm development, and defining science and engineering products and associated performance requirements; coordinating campaign
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, payload, forward and retrieval algorithms, level 0 to level 1 algorithms, etc.); supporting the development of generic building blocks and modules for end-to-end performance simulators, aiming for maximum
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of the University of Groningen in The Netherlands. The position is available within the research project "Aggregating Safety Prefer-ences for AI Systems: A Social Choice Approach." The project aims to develop formal
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of the University of Groningen in The Netherlands. The position is available within the research project "Aggregating Safety Prefer-ences for AI Systems: A Social Choice Approach." The project aims to develop formal