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Field
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comprehensive interdisciplinary Institute now housed within the UTRGV College of Sciences, which has generated substantial extramural funding for many years. The Department is home to a PhD program in Human
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, parallel storage systems and scientific data management. Recent research project details and outcomes can be found in computer systems conference proceedings, such as HPCA, FAST, SC, DSN, HPDC, IPDPS, and
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State University of New York University at Albany | Albany, New York | United States | about 11 hours ago
vibration isolation). In parallel to the benefits of quantum computing, artificial intelligence and neuromorphic computing seek to emulate the massively parallel, highly efficient computing capacity
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: Information Systems Engineering: retrieval, knowledge representation, requirements specification, applications programming Health Informatics Artificial intelligence and cognitive models Sequential, parallel
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conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry, Computational Science
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-reviewed venues and conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry
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of capabilities such as AI training and inference at scale, and tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics
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– in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in materials science, applied mathematics, computer science, or an AI related field completed within
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Communications and Scientific Content, and in parallel also to the Principal Investigator (PI), and Director of Research Operations. This reporting structure reflects the varied responsibilities of this position
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- Posting may close at any time) Job Summary We are looking for MS and PhD students with experience and interest in state-of-the-art data management technologies, high performance computing, memory management