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- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
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single-mode and multimode semiconductor laser arrays Optimization and acceleration of existing simulation codes Parallel computing and high-performance computing (HPC) GPU acceleration, where
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enter the lab, how they are stored, documented, and harmonized, and how the team's analyses run on the high-performance computing resources. You will work closely with the lab's Senior Scientist, who
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analyses run on the high-performance computing resources. You will work closely with the lab's Senior Scientist, who oversees the data-sharing agreements with our partners, and with the PI, postdocs, and
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numerical accuracy and stability. The position provides an opportunity to work at the intersection of computational mathematics, nonlinear dynamics, high-performance computing, and experimental photonics
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HYBIRD framework within the Geotechnical Engineering Group. Additional training in high-performance computing and version control will be provided through the University of Sheffield HPC Centre
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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 2 months ago
: Comprehensive health & life insurance Relocation support for international faculty Build State-of-the-Art Research Facilities: Cutting-edge AI labs and high-performance computing Live in Abu Dhabi: World’s safest
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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 2 months ago
: Cutting-edge AI labs and high-performance computing Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities Industry & Government Collaborations: Work with
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. Disciplines where we are seeking lecturers in lieu of GSIs include: Computational Chemistry Scientific Computing Bioinformatics Machine Learning/Deep Learning High Performance Computing Complex mathematical
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Department: Col of Engineering and Computing Classification: Research Staff 12-month Job Category: Research Staff Job Type: Full-Time Work Schedule: Full-time (1.0 FTE, 40 hrs/wk) Location
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learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple-instance learning or high-performance computing is an