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Field
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) Country Sweden Type of Contract Temporary Job Status Full-time 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
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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, computer science, simulation science with a strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills
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-scale deformation and microstructural analysis - Targeted petrochronological studies on magmatic and deformation events - Integration with regional geophysical models developed in parallel projects
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advertisement Job description University of Stavanger is seeking a jazz/improvised music practitioner to work fulltime as a research fellow in our PhD programme in Artistic Research at The Faculty of Performing
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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via joint activities with EU and UK cybersecurity hubs, preparing you for careers in trusted electronics, AI security, and national critical infrastructure protection. Graduates from this programme will
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 1 month ago
-09731 Requirements Skills/Qualifications Candidate profile - Master degree Computer Sciences. - Experience in scientific programming (e.g., Python, C++, Fortran, Julia) and parallelization