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Field
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using GPU/CUDA clusters for AI/ML and/or image processing. Proven ability to work in a dynamic environment and support large data systems. Effective documentation skills, including ability to prepare
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, microscopy, or image analysis Knowledge of large image formats like TIFF or SVS Understanding of GPU acceleration or multithreading in C# Solid understanding of UI/UX design principles Familiarity with
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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data
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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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, such as aircraft tugs, ground power unit (GPU), lavatory service cart, de-icing cart, forklift, golf cart, UTV, and airport shuttles and vehicles. Renders grounds maintenance, such as mowing, cutting trees
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medicine and drug discovery. The King's AI+ strategic investment recruiting 20 AI focused fellows and adding £2m of next-generation GPU capacity to King's Computational Research Engineering and Technology
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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-scale training of a high-performance foundation model using a dedicated GPU cluster Fine-tuning the pretrained model on real-world health data from lifespin’s proprietary database Collaborating closely
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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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reactions. Development and deployment of graphical user interfaces (web apps, desktop apps) Parallel computing (GPU & CPU). Familiarity with cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes