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Field
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role We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training
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of advanced language models and derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable
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inference pipelines using modern ML tooling (e.g., PyTorch/TensorFlow/JAX), version control, containers, and HPC/GPU resources. Support the publication of intermediate data products, models, code, and
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optimizing compilers, the classical and quantum fragments are separated in efficient implementations adapted to the changing QPUs and GPUs architectures. The candidate will work at the intersection
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the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM
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for mechanical, electrical, cooling, and infrastructure systems that underpin Cornell's computing environment, including High-Performance Computing (HPC) and Graphics Processing Unit (GPU)-intensive workloads
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, proteins, chemical structures, geospatial, oceanographic, or heath record data. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Familiarity with RESTful web
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skills, with the ability to translate complex AI concepts into accessible solutions for diverse stakeholders; (f) possess knowledge of Graphics Processing Units (GPUs) and Neural Processing Units (NPUs
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, 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 to help you
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clusters, cloud computing, or GPU acceleration. Strong mathematical background in linear algebra, probability, and statistics. Prior research experience with publications or preprints. The University