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analysis, as well as defining which materials-focused parameters are needed to generate and inform accurate real-world and computational models. IPI staff will work with the Fellow to identify materials
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-scale innovations toward scalable manufacturing solutions. Design, execute, analyze, and document experiments to evaluate materials, manufacturing processes, equipment parameters, and battery cell
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and staff computing, cross-platform (Mac/Windows) computer labs, AV systems, managed print services, tablet checkout resources, peripherals, and specialized hardware and software used in academic and
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• SLAM, autonomous driving and mobile robotics • Remote sensing, image/video processing and computer vision • Object detection, tracking and classification using deep learning • Monitoring
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recognition, brain-inspired or spiking neural network approaches, predicting material properties, optimizing processing parameters for next-generation energy technologies, analysis of "big data" generated from
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electronics. Applicants must have a Ph.D. in Electrical Engineering, Computer Engineering, and/or Microelectronic Engineering or a closely related field. The candidate’s research must specialize in one or more
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for biomedical systems. Applicants must have a Ph.D. in Electrical Engineering, Computer Engineering, and/or Microelectronic Engineering or a closely related field. The candidate’s research must specialize in one
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with degrees in Computer Engineering, Electrical Engineering, Robotics, Mechatronics, or closely related engineering disciplines are encouraged to apply. A PhD in Engineering Education or experience in
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for faculty and staff within the college Participate in admissions and recruitment programs as assigned. Participate in orientation programs as required. Stay current with processes, technology, and computer
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office computer software such as Microsoft Office Skill in written and verbal communication Skill in repair of electrical meters and use of test equipment Ability to read blueprints and electrical