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Field
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Post-Doctoral Associate Employment at NYUAD
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. Develop advanced optimization, control, or machine learning strategies for distribution systems; validate these strategies using hardware-in-the-loop or real-time grid simulators. Develop optimization
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MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless communications Hardware-constrained signal processing
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Advantage . Qualifications: Minimum Qualifications: Applicants must meet minimum qualifications at the time of hire. A minimum of a PhD in relevant scientific area such as Physiology, Molecular Biology and
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with both research and teaching responsibilities. Preference will be given to candidates whose expertise aligns and strengthens the research of the Department. The successful candidates must have a PhD
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artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
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opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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package for employees. Learn about NREL’s critical objectives: NREL's Mission and Vision . Job Description The Catalytic Carbon Transformation & Scale-Up Center at National Renewable Energy Laboratory (NREL