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integrated with the computational research led by Ioana Ilie. The two PhD candidates will work across the work packages in parallel so that experiments and computational simulations continuously inform each
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Deadline 4 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type 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
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
23 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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) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Is the
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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 Description The successful candidate will join the
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on ship design, naval control systems and in shipping management. Within the project we are aiming to recruit up to ten PhD students and one or two Post Docs to work in parallel across the core engineering
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at TU Delft, supervised by Prof. Kofi Makinwa and Dr. Padmakumar R. Rao. You will collaborate closely with the parallel metaoptics PhD researcher, SRON and the other INTERPRETER partners. Job
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Oettingen in Bayern, Bayern | Germany | 3 months ago
Student in Cancer Biology and/or Bioinformatics Reference number: 2026-0129 We study the molecular basis of cancer through an integrated approach spanning genomics, molecular biology and computational
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the energy and physical resource consumption of AI models continues to scale, there is an increasing need for new computational paradigms that draw on the efficiency and parallelism of biological