80 power-electronic-"https:"-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
, Northwestern University, and Lawrence Berkeley National Laboratory to address grand challenge problems in materials for next-generation microelectronics applications. The position resides in the Theory
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. Conduct power profiling, energy-per-inference measurements, and latency benchmarking on physical edge hardware platforms. Build strong collaborations within ORNL and with the neuromorphic computing and
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implementing signal processing techniques. Experience working with benchtop instrumentation, including power supplies, oscilloscopes, optical spectrum analyzers, etc. Experience working at or collaboration with
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Model, working closely with the experimental team to understand this device’s PMI physics and optimize performance of the device in its upcoming campaigns. The position resides in the Power Exhaust and
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milestones. Major Duties/Responsibilities: Utilize techniques such as optical microscopy, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM
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with the ability to work independently and to participate creatively in collaborative teams across the laboratory. Ability to function well in a fast-paced research environment, set priorities
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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communication skills. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory. Ability to function well in a fast-paced research
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and aspects related to safety and best practices. The candidate will make extensive use of state-of-the-art imaging, spectroscopy (Raman, electron microscopy, infrared, etc.) and scattering methods