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Field
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position within a Research Infrastructure? No Offer Description The position targets the design and evaluation of novel architectures, programming paradigms, and parallel algorithms for AI accelerators
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in
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- and neuron-targeting anti-obesity drugs in these ex vivo systems. In parallel, you will collaborate with a team of postdocs, PhD students, and technicians working with genetic animal models
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
is designed for candidates who have completed their PhD within the last two years and have experience as postdocs or industry researchers. This position offers a 12-month term with potential
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. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 administrative
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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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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs
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for the electrochemical community. In this work, we aim to study the mechanical properties of electrodes during charge/discharge cycles, in parallel with the ionic insertion/deinsertion phenomena observed by
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. Candidates must have received their PhD within the past three years. Postdoctoral Research Associates will pursue their own research, contribute actively to the intellectual life of the Center by participating
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for an accurate simulation of time-dependent flows, enabling sensitive applications such as aeroacoustics. Furthermore, the high scalability on massively parallel computers can lead to advantageous turn-around