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Field
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sitting within a leading programme of clinical, health and bioinformatics at the South London and Maudsley (SLaM) Biomedical Research Centre (BRC) and forms a key component of both the Centre
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using
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School: Faculty of Arts and Sciences Department/Area: Kempner Institute for the Study of Natural and Artificial Intelligence Position Description: The Engineering Fellowship Program at Kempner Institute
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Based within the School of Computing and Mathematical Sciences on the World Heritage site at the Old Royal Naval College, Greenwich, you will be part of the Centre for Safety, Resilience and Protective
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programme of clinical, health and bioinformatics at the South London and Maudsley (SLaM) Biomedical Research Centre (BRC) and forms a key component of both the Centre for Translational Informatics
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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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. Communicate software engineering concepts to project teams with varying levels of expertise. Serve as a liaison with Princeton Research Computing staff on GPU cluster-related issues. Professional Development
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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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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software delivered to sponsors outside of ARL:UT. Other related functions as assigned. Required Qualifications Bachelor’s degree in Computer Science, Computer Engineering, or other related discipline