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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 days ago
into the high-performance code hawen (https://ffaucher.gitlab.io/hawen-website/ ) with the support of the development team, enabling their application to real-world applications. The program will be divided
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Mar 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Starting Date 1 May 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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, cyber-physical systems, real-time systems, autonomous systems, middleware, parallel computing, operating systems, Edge AI or AI in cyber-physical systems; Demonstrate strong analytical, programming, and
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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Framework Programme? Not funded by a EU programme Reference Number CNS2023-145425 Is the Job related to staff position within a Research Infrastructure? No Offer Description Descifrando la vulnerabilidad
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parallel, it produces new, high-resolution computer models of the warm Last Interglacial period. Finally, PAST creates new knowledge by synthesising these two approaches through advanced statistics. This PhD