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(Java) and others. 4. Translate complex research requirements to suitable software solutions, reporting progress to relevant research stakeholders as appropriate. 5. Oversee multiple independent
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, and tooling support across multiple clustered infrastructures, we facilitate Lab-wide R&D projects. Our HPC clusters range in scope from just a handful of nodes to over fifty-thousand cores. We partner
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free text of both biomedical literature and electronic patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling
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well as an integral member of the AI Lab and the research community it supports. You will work with a diverse group of faculty, postdocs, and students from multiple disciplines. If you are passionate about advancing AI
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patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling for ML / LLM algorithms working over free-text clinical
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models, (d) experience in using high performance computing systems with multiple nodes and GPUs and (e) drought metrics. Familiarity with Texas water resources and management practices. Experience working
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models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing new models of brain circuits and function; and learning software engineering
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CSRPS. The successful candidate will have a capacity to conduct high quality research in multiple and coupled challenges in the following research areas: fire and combustion modelling, dynamic coupling
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expert with deep understanding of technical challenges associated with research across multiple disciplines. In this role you will deliver a service with the potential to support research in multiple ways
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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