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optimization models for electric vehicle fleet charging planning. Activities: • Apply operations research methods (linear and mixed-integer programming, dynamic optimization, stochastic optimization) • Integrate
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candidate will contribute to cutting-edge research in optimal control theory, differential game theory, mean-field game theory, and mean-field-type game theory, developing advanced mathematical frameworks and
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projects focused on optimization, data analytics, and control of power distribution systems. This position offers the opportunity to collaborate closely with utility company partners and national
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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for predictive modeling, high-dimensional optimization, uncertainty quantification, forward and inverse design, including the development of Digital Twin components, under the supervision of Prof. Douglas H
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and 3D finite element modelling (COMSOL, CST) of the optical control process for materials. -Integration of the optimal compositions into simple test structures to directly evaluate electrical switching
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observations be assimilated into predictive ecosystem digital twins? Can autonomous AI systems optimize environmental monitoring and experimentation? Outstanding U of A benefits include health, dental, vision
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, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy-efficiency to realized efficient Embodied/Edge-AI implementations. A key focus will be
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motivation to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control
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closely related field at the time of appointment. Preferred qualifications ● Domain knowledge in energy studies, power systems, renewable energy grid integration, and optimization models. ● Extensive