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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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Application Deadline 23 Sep 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2025 Is the job funded through the EU Research Framework Programme
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Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number 101169263 Is the Job related to staff position within a Research Infrastructure? No Offer Description The DESIRE project
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. These works are recorded and performed both at the residential facility, where the participants live, and at Museum Overtaci, where they are shared with networks and the public. The project will investigate how
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30 Aug 2025 Job Information Organisation/Company Umeå universitet Department Umeå University, Faculty of Science and Technology Research Field Computer science Researcher Profile Recognised
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23 Aug 2025 Job Information Organisation/Company SINTEF Department Digital Research Field Computer science All Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Established
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the EU Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number 101169263 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned
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5 Sep 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Country Sweden Application Deadline 23 Oct
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 15 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially