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                IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 21 days agofor acceleration of parallel applications in the High Performance Computing (HPC) environment, · work in the international team focused on development and optimization of parallel codes under national and 
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                -edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training 
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                Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs 
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                scientific computing. You are proficient in several languages (Python, C/C++, or Fortran), with extensive knowledge in AI/ML and parallel programming (GPU, multi-threading, etc.). You have strong software 
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                applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics 
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                35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No 
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                Research Framework Programme? Not funded by a EU programme Reference Number 2025/CP/203 Is the Job related to staff position within a Research Infrastructure? No Offer Description Grant/funding reference 
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                conferences to disseminate research findings, and mentoring junior team members in preparation for their presentations. In parallel, the principal investigator (PI) will provide mentorship aimed at supporting 
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                distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse