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Mateo Daniel Roig Greidanus

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PhD Opportunities in Power Electronics, Control Systems, and Cyber-Resilient Energy at Kansas State University Kansas State University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Available

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Country

United States

University

University of Kansas

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Keywords

Computer Science
Electrical Engineering
Microgrid Technology
Model Predictive Control
Optimisation
Power Electronic
Digital Control
Renewable Energy Systems

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About this position

Mateo Daniel Roig Greidanus, Assistant Professor at Kansas State University, is recruiting two PhD students to join the REACT (Resilient Energy and Advanced Converter Technologies) Power Electronics Laboratory. The preferred start is Summer or Fall 2027.

The research focuses on two directions: physics-based modeling and Edge AI for cyber-resilient power electronics, and advanced control and optimization of power-electronic systems. Projects may involve converter-level digital twins, physics-informed monitoring, embedded AI for anomaly detection and diagnostics, cyber-physical resilience in interconnected power converters and microgrids, real-time predictive control, coordination, distributed and centralized control architectures, and emerging quantum-assisted optimization methods.

Both PhD opportunities include analytical modeling, simulation, embedded control implementation, and experimental validation using power-electronic hardware. Applicants should hold a master's degree in Electrical Engineering or a related field and have strong preparation in power electronics, converter modeling, and control, along with knowledge of embedded digital control using DSPs, microcontrollers, or FPGAs. Experience with converter design and testing, machine learning, Edge AI, advanced optimization, or quantum computing is advantageous.

Interested candidates should email their CV and a brief description of their research and experimental experience to [email protected]. The research group is the REACT Power Electronics Lab at Kansas State University, USA.

Funding details

Available

What's required

Applicants must have a master's degree in Electrical Engineering or a related field, a strong background in power electronics, converter modeling, and control, and knowledge of embedded digital control using DSPs, microcontrollers, or FPGAs. Preferred qualifications include hands-on experience with power-converter design, implementation, and testing; experience or interest in machine learning, Edge AI, or advanced optimization; and familiarity with quantum computing.

How to apply

Email your CV and a brief description of your research and experimental experience to [email protected]. Candidates whose qualifications align with the opportunities will be contacted.

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Assistant Professor

University Name
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Research Interests

Renewable Energy Systems

Electrical Engineering

Microgrid Technology

Computer Science

Optimisation