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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP), Horovod, or DeepSpeed, and in
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Systems {LIMS); Eclipse IDE; SG E, PBS or other batch job schedulers; Relational Database Management Systems {RDBMS) and SQL programming; Message Passing Interface {MPI) programming; CUDA/OpenCL/G PU
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not mandatory, expertise in quantum platform software such as Qiskit or cuda-q. *Numerical expertise with classical simulations of quantum circuits, including tensor-network based approaches
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for quantum entanglement and decoherence. Desired, though not mandatory, expertise in quantum platform software such as Qiskit or cuda-q. Numerical expertise with classical simulations of quantum circuits
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: A relevant tertiary qualification or relevant experience. Experience in a financial management role with reporting experience in a large, complex organisation. Desirable: Vendor training in CUDA/GPU
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at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo-project/ginkgo
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written. Additional Qualifications ConsideredEmpty heading Knowledge of CUDA. Knowledge of PyTorch or a similar deep learning framework Experience writing software trigger infrastructure. Experience
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, the Musculoskeletal Biomechanics Lab, the Data-Driven Modeling Lab, the Heat Transfer & Applied Thermodynamics Lab, and the MultiPhase & BioFluids Lab. More information can be found by visiting https://eas.uccs.edu/mae
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researchers to integrate computing techniques into research activities using common HPC programming languages, tools, and techniques including Fortran and/or C/C++, MPI, OpenMP, CUDA An equivalent combination