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computing concepts, including parallelization, memory management, and performance optimization. Familiarity with heterogeneous computing technologies (e.g., GPUs, accelerators) and related frameworks (e.g
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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, reproducible data products and extracts to support research teams and strategic initiatives. ● Design and implement informatics strategies that integrate geospatial attributes, place-based linkage, and remote
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later as an individual effort. Explore Uses of AI in Education: tracks programming and support materials related to AI at other higher ed institutions, looking for opportunities for parallel programming
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3 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire Interdisciplinaire des Energies de Demain Research Field Chemistry Chemistry » Computational chemistry Researcher Profile
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Engineering Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 30 Apr 2026 - 21:59 (UTC) Country Sweden Type of Contract Not Applicable Job Status Full-time Is the job funded
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) Established Researcher (R3) Application Deadline 3 May 2026 - 22:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded
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4 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique de la matière condensée Research Field Physics Chemistry » Computational chemistry Researcher Profile First
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science, or related fields. At least four years of relevant postdoctoral research experience. Desired skills/knowledge: Knowledge of high-performance computing concepts, including parallelization, memory management
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 1 day ago
and relevant work experience. Preferred Education Skills and Experience: Experience in High Performance Computing related technologies such as schedulers, parallel computing, storage systems