82 algorithm-development-"Multiple"-"Simons-Foundation" "Prof" positions at University of Groningen
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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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Doctoral Network addresses these challenges by developing a neuromorphic platform that is inherently self-aware in terms of energy consumption, secure operation, and system reliability. As part of
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Doctoral Network addresses these challenges by developing a neuromorphic platform that is inherently self-aware in terms of energy consumption, secure operation, and system reliability. As part of
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Doctoral Network addresses these challenges by developing a neuromorphic platform that is inherently self-aware in terms of energy consumption, secure operation, and system reliability. As part of
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for partners of new faculty members moving to Groningen. Unsolicited marketing is not appreciated. Information For information you can contact: Prof. dr. Iris Vis, i.f.a.vis@rug.nl (please do not use the email
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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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researchers to develop their own individual talents. Among the best research universities in Europe, we join forces with prestigious partner universities and networks around the world, the University
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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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collections interact with power, knowledge, and ongoing processes of heritagization. The candidate is encouraged to develop new methodologies that center community-led, ethical, and innovative approaches
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machines that will lead to demonstrations with practical relevance. Specifically, this project in the group of prof. Feringa aims to address two key challenges: 1) How can we amplify the work of molecular