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stakeholders, and collaborate with other scientists, other ORISE fellows, Hub leadership, and partners to determine potential solutions and pathways for optimizing productivity. Learning Objectives: The Fellow
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resilience and energy-savings. Learning Objectives: The Fellow will build skills in: Building relationships with stakeholders Tool generation for producers and technical exerts Creating educational materials
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, identify tasks, and establish responsibilities; (b) Participate in team meeting discussions and present research results; (c) Use/learn establish research techniques, like optical microscopy, electron
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, topological data analysis, and machine learning to understand data relationships generated by either our simulations or from experimentally acquired neuroimaging data. Applicants should have a strong
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Analysis, Bioengineering, Computer Science, Electrical Engineering, Machine Learning, Mechanical Engineering, Neuroscience, Physiology, Probability and Statistics. The Associate must have an interest in
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dynamic environments and situations. HRED leverages human-robot interaction, human-informed machine learning, human cognition and adaptive teaming to improve human-autonomy teaming for future Army teams
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, human-informed machine learning, human cognition and adaptive teaming to improve human-autonomy teaming for future Army teams. About ARL-RAP The Army Research Laboratory Research Associateship Program
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their professional experience by learning and developing new nano-mechanical characterization techniques to probe material structure-property relationships at the nano-scale are encouraged to apply. Preferred