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, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch - background knowledge in computational
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Applicants must hold a relevant master’s degree in telecommunications, computer networks, computer science, or a closely related field, with a strong background in computer networking and distributed systems
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1 Mar 2026 Job Information Organisation/Company Fundació Privada I2CAT Department Software Networks Research Field Technology » Telecommunications technology Researcher Profile First Stage
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science background, preferably in algorithm design, system programming, networking, operating system, and computer architecture. Experience in low-latency RPC, network stacks, distributed systems, host data plane
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 13 days ago
communication networks and the storage capabilities in these clusters do not follow such fast trends. As a result, computing nodes produce outputs faster than what can be stored or sent to process elsewhere
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and failure risk of their networks. Within the Wetsus Smart Water Grids program, this project aims to support a transition from reactive leak detection to proactive monitoring of drinking water
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rules. Please, refer to the section “Applicable Unit Contributions” (page 118 and following) of the Horizon Europe Work Programme 2023-2025 for MSCA-DN actions, available at the following link: https
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optimally integrated into a geothermal data-assimilation workflow. Where to apply Website https://brgm-recrute.talent-soft.com/job/job-phd-in-computational-geosciences_4… Requirements Research
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Would you like to contribute to understanding how social network connections and
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of neuronal spontaneous activity and network theory, to produce biologically plausible computational models of connectivity in the newborn brain, using state-of-the-art multimodal neonatal and adult MRI data