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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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a functional. A key challenge lies in determining the regularity of solutions relative to parameters. For practical applications, choosing numerical methods with optimal convergence rates should align
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prediction of queue dissolution by combining traffic flow theory with data from roadway and AMOD sensors, nonlinear optimization of the signal plan, cooperative control of traffic signals and AMOD vehicle
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computational methods, that leverage high-performance computing power, to develop advanced tools. The successful candidate will be expected to develop machine learning methods that integrate physical
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positioned team of experts in the field of photonic components, laser sources, and nonlinear converters. You will contribute to the improvement of fiber components and new designs. You will independently work
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on electric machine drives and power converters. Our work spans from fundamental modelling and analysis to advanced control design and system optimization. Our specialty is developing embedded control
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | about 2 months ago
to inform policy decisions that balance economic performance with environmental conservation. Project overview The primary objective is to develop realistic multi-species fish models that determine optimal
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team led by Univ. Prof. Olga Mula. Our group’s work sits at the forefront of numerical analysis for Partial Differential Equations, enriched with data-driven methodologies -- a powerful combination
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Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J
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to invite applications for a University Assistant (Praedoc / PhD Candidate) to join the research team led by Univ. Prof. Olga Mula. Our group’s work sits at the forefront of numerical analysis for Partial