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Field
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Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion
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, trauma and history are entangled. Job description: In close coordination with the project management and the other project staff, the computer-assisted analysis of interviews with Holocaust survivors will
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Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion) in FPGA design, machine learning or a
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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studying deformation mechanisms in refractory alloys as via atomic-scale calculations as well as application of machine learning to materials discovery The ideal candidate will have the following
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expected to teach relevant courses at the bachelor’s and master’s levels with supervision from colleagues. Lastly, you will be advising students at all levels, including Master and PhD students
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 6 hours ago
, machine learning and statistical methods to elevate impacts research. There is also opportunity to work at the nexus of water and agriculture, as well as in risk management for suburban landscapes. Location
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources