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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
, including the 17,000-core Longleaf cluster optimized for I/O intensive workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC
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. Preferred Qualifications Experience with: C/C++, Python, MATLAB, ROS 1 and 2, OpenCV, Unity, GPU programming, linear and nonlinear control theory, supervised, unsupervised and reinforcement learning, Torch
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations. This advancement will enable high-fidelity
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its
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training in the second area are encouraged to highlight this in their application. Experience with high performance computing and GPU acceleration tools (e.g. CUDA) and deep learning frameworks, such as
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physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the abovementioned fields. What we offer State of the art on-site high performance/GPU compute
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, Matlab Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
environment Access to state-of-the-art tools and computational infrastructure, including CPU/GPU clusters Opportunity to contribute to cutting-edge research in plant evolution and genomics Support