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8 Oct 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2027 Is the job funded through the EU Research Framework Programme
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algorithms, validated in real-time simulations and experimentally in collaboration with industry. The project: This project looks at the development of electromechanical friction wheel braking (EMB) systems
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
31 Jul 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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include theoretical results, mathematical proofs, and computational algorithms, as well as open-source software and validation through simulations and analysis. Experimental demonstration is an option if it
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Application Deadline 9 Sep 2026 - 23:59 (Europe/Brussels) Country Slovenia Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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for the quantum-classical control and readout interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and
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IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT
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, an ambitious ERC-funded research program that aims to develop and evaluate personalized donor health protection strategies for blood and plasma donors. As demand for plasma-derived medicinal products continues
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expertise in artificial intelligence, computer vision, human-computer interaction, and psychology. Its technical core lies in developing robust and adaptive visual speech recognition models. Close
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working