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observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process
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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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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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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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. 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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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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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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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
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-biology-neurobiology-and-anatomy/people/xuelin-lou-phd ). Postdocs are essential to the scholarly mission of the mentor and host institution, and thus are expected to have the freedom to publish the results