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Field
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applications for computer vision. Experience using C++ to develop and run software applications. Experience using GPU-accelerated ML and related frameworks. Experience with Docker or other containerized
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. Experience using C++ to develop and run software applications. Experience using GPU-accelerated ML and related frameworks. Experience with Docker or other containerized application development platform Three
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Strong foundation in CFD, Programming proficiency such as Python, AI/ML techniques, Experience with parallel computing on CPU/GPU cluster, use of CUDA, MPI is a plus. Experience Experience with open-source
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generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab, which has multiple test machines with GPUs and AI
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showcases and visualisations; and scaling and optimising data science and AI research to leverage HPC and GPU infrastructure. This post is full time and open ended (permanent) Apply online at: Research
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an early member of a friendly, multi-disciplinary team. The project will involve significant coding using the Julia package Molly.jl on both CPU and GPU, as well as addressing relevant computational and
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and train CNN and SNN models utilizing frameworks such as Keras, PyTorch, and SNNtorch Implement GPU acceleration through CUDA to enable efficient neural network training Apply hardware-aware design
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neural networks to harden object detection and semantic segmentation, as well as maintaining the real-time performance of the hardened AI computing on embedded GPUs (NVIDIA Jetson AGX Orin). RGB camera and
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performing routine maintenance on lab computing resources (e.g., Linux servers, GPUs, networked workstations). (10%) Performs other tasks, duties, and responsibilities as required Minimum Qualifications
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& GPUs — and deep integration with clinical data including electronic health records A diverse array of ongoing research, education, patient care, and community centered activities that require increasing