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Senior R&D Staff - Physics-informed Machine Learning Scientist for Autonomous Self-driving Laborator
Requisition Id 12780 Overview: We are seeking a Machine Learning Scientist who will focus on research and development of new physics-informed machine learning algorithms, as well as writing and
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research experience beyond the PhD. A well established track record of research in an area relevant to one or more areas of expertise of the group. Knowledge of state-of-the-art machine and deep learning
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completed in the last five years. Hands-on experience with machine learning, process modelling, and industrial data acquisition systems is very valuable. This position may also require access to technology
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approaches for scientific data analysis and/or the latest machine learning approaches, including deep learning models. Experience working with DOE National Laboratories (or similar R&D organizations). Special
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to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation. We are seeking a Machine Learning Scientist who will focus on research and development
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modeling and experiences in machine learning Strong background in modern techniques in fabrication of nano- and microfluidics An excellent record of productive and creative research as demonstrated by
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with machine learning, particularly as applied to hydrology or other environmental systems Experience developing software for, and running software, in a cluster computing environment Experience with
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opportunity to creatively use interdisciplinary methods from computational data science, machine learning, geographical information sciences, and many other topics to help frame and solve the above problems on
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analytics, and machine learning, the Grid Interactive Controls group delves deeply into understanding intricate grid-edge operations. Researchers are dedicated to laying the groundwork for optimal X2G
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scientists, engineers, enterprise software developers, and machine learning experts at both neutron research facilities. We are seeking applicants to study materials science & engineering using neutron