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for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations. This advancement will enable
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, Probabilistic Inference, Algebraic Topology and Wavelet analysis theory. Familiar with Matlab/Python/C++ programming. Experience with Pytorch and multi-GPU model deployment. Experience in analyzing complex
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, Probabilistic Inference, Algebraic Topology and Wavelet analysis theory. Familiar with Matlab/Python/C++ programming. Experience with Pytorch and multi-GPU model deployment. Experience in analyzing complex
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
further GPU porting. The exploration of C++ programming models for performance portability, such as Kokkos or StarPU, will form a second part. A comparative study will evaluate the different implementations
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: Multiphysics Simulation of Hemodynamics, Treatment, and Long-Term Perspective of Cerebral Aneurysms Using Lattice Boltzmann Methods. As part of the second phase of the DFG funded Priority Programme SPP2311
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, with PyTorch and/or other GPU programming tools is also necessary. You should have completed all requirements for your PhD by the time you are hired. How to Apply: Candidates who have most, but not all
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Open Position: (Postdoctoral) Researcher (m/f/d) Model Building for SPM Images of Macro(bio)molecules Job Code: 03.25 Your project: Build and test a GPU‑accelerated program to detect and interpret
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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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Max Planck Institute for Solid State Research, Stuttgart | Stuttgart, Baden W rttemberg | Germany | 3 months ago
Job Code: 03.25 Job Offer from February 14, 2025 Open Position: (Postdoctoral) Researcher (m/f/d) Model Building for SPM Images of Macro(bio)molecules Your project: Build and test a GPU-accelerated
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proteins to specific locations on the genome. The project involves grid preparation and screening, data collection and image processing using the Emory cryoEM core and our lab’s cluster (200 TB and 8 GPU