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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 21 days ago
operates the first Czech quantum computer named VLQ. https://www.it4i.cz/ Activity description: development of methods for acceleration of parallel applications in the High Performance Computing (HPC
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++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA, OpenCL, or equivalent). Familiarity with
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-SofT project, the recruited person will: - design novel algorithm for large-scale block-sparse tensor computations that are suited for massively parallel accelerated supercomputers. - investigate the use
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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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20 Feb 2026 Job Information Organisation/Company Università degli Studi di Trento Research Field Computer science Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage
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working on related topics Participate in teaching and supervision activities, in line with the candidate's profile and interests The research activities will be hosted by the Parallel Computing and
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simulation environments and real-world deployments 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
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research projects. In parallel, they participate in the comprehensive BIGS DrugS education programme, which includes workshops, lectures, colloquia and symposia. Mentoring is performed by two experienced
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of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility
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. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development