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conducted implementations of algorithms and simulations using contemporary GPU hardware, or Profound knowledge and experience of the DUNE software environment (https://dune-project.org/ ) (knowledge and
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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
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sciences. The recruited Ph.D. students will integrate into the AIMLeNS group, and enjoy priority access to excellent national GPU resources such as Alvis and Berzelius. We are front-runners in this dynamic
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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using clusters like UPPMAX and GPUs for high-performance computing and parallel computing using clusters like UPPMAX and GPUs for high-performance computing are essential. While not required, experience
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Excellent programming skills in PyTorch/JAX and experience working with GPUs and high-performance clusters. Strong mathematical skills with excellent understanding of statistics (e.g., hypothesis testing
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precision algorithms for CPUs and GPUs. Performance engineering and analysis including application profiling, benchmarking to identify performance bottlenecks. Verification, and validation of the developed
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scenarios Convolutional neural networks for computer vision require substantial computing resources and introduce significant latencies even in modern GPU systems. This project investigates neuromorphic
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models, LLMs and Transformer architectures Excellent programming skills in PyTorch/JAX and experience working with GPUs and high-performance clusters. Strong mathematical skills with excellent
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spatial datasets efficiently. Research‑grade software engineering skills (version control, testing, reproducibility, documentation); open‑source contributions are meriting. Experience with GPU/high