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. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures without changing the code. Our research team at NYUAD (New York
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: Strong expertise in signal processing for wireless communication systems, including modulation and coding techniques on the physical layer of a radio, array antennas and their use in multiple input
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components of key US cross-agency data and AI for Science efforts and initiatives. We seek a candidate with specialized knowledge developing scalable and robust computer systems, working with high performance
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pipetting, buffer and solution preparation, PCR, gel electrophoresis, and sterile technique Proven ability to manage multiple tasks and keep parallel experiments on track Strong teamwork and communication
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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
and combinatorial synthesis workflows, including high-throughput solution synthesis, microdroplet printing and processing Design and execute automated synthesis experiments using robotic platforms
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, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together
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. Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research