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simulation runtimes. During the PhD programme, a student would be expected to explore and analyse the limitations of possible solutions for parallel simulation of massively multicore computers. During
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integrity, provenance, and reproducibility across datasets. 3. Engineer and optimize high-performance data workflows for large-scale biomedical datasets using Python-based tools and parallel computing
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Italy | about 22 hours ago
3 Apr 2026 Job Information Organisation/Company ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA Research Field Computer science » Informatics
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2 Apr 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Computer science Researcher Profile Established Researcher (R3) Application Deadline 17 Apr 2026
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approaches include MHD, Vlasov, and hybrid codes run on computers ranging from PCs to massively parallel computers, while analytical work involves linear and nonlinear instability theories. Location: Goddard
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 3 hours ago
. Preferred Education, Knowledge, Skills and Experience Experience in High Performance Computing related technologies such as schedulers, parallel computing, storage systems, or scientific applications
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with the nano-drones of the University’s SwarmLab The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT, headed by Prof. Grégoire Danoy. PCOG conducts
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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