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AI-enabled digital technologies for the resilient operation of power systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline
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Master Thesis - Decoding Occupancy: Classifying User Activity from Building Power Consumption with Machine Learning At the Institute of Climate and Energy Systems Engineering (ICE-1) we focus on the
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Your Job The increasing complexity of future power systems, driven by renewable energy integration, power electronics, and distributed energy resources, requires computational methods capable of
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Details Title Postdoctoral Fellowship in Power and AI Systems School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science/ Electrical Engineering
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neural networks, and physics-informed machine learning in power systems Set up benchmark grids and generate or process suitable simulation data for power-flow, voltage-prediction, or state-estimation
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charging systems. Proficiency in MATLAB and/or Python. Experience in student supervision and teaching. Preferred: Experience in dynamic modeling and simulation of power system components. Familiarity with
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Systems on a research project investigating interactions between the power grid and turbine-generators, with Olkiluoto 3 nuclear power plant as the main case study. Olkiluoto 3 is one of the largest
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future sustainable and resilient electric power systems, with particular emphasis on: Flexibility and resilience in electric power systems, Integration of energy storage and renewable power generation
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researcher to join the Department of Electrical Engineering and Automation at Aalto University, Finland. You will work in the Research Group of Power Transmission Systems on a research project
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support informed decision-making for integrated energy systems. Your tasks in detail: Analyse the impacts of future energy transition pathways on the planning and operation of European power and gas