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phlebotomy. Additionally, the GPU is home to the GI Division's Motility program offering short and long motility studies, Bravo, Impedance Probes and EndoFlip diagnostic tests. The GPU is also home to
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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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Sheffield to enable massively parallel processing of ABMs on NVIDIA graphics processing units (GPUs), without the need for specialist understanding of GPU programming or optimisation. This project will
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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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strategies for programming, modeling, and integrating reconfigurable/spatial architectures, such as FPGAs and ML accelerators, within heterogeneous ICT ecosystems.Reconfigurable and Spatial hardware, such as
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Applicable 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 Research Infrastructure? No Offer Description The research
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programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
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commonly used on Unix systems. 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
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high-performance GPU cards for enhanced processing capabilities. For more details, please refer to: https://robinson.gsu.edu/academic-departments/insight/innovation-labs/insight-lab/ Disclaimer: This job
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funded through the EU Research Framework Programme? Horizon Europe - ERC Reference Number 101220027 Is the Job related to staff position within a Research Infrastructure? No Offer Description Project: GPT