Join the SPARC project at Eindhoven University of Technology as a PhD researcher and contribute to the development of advanced probabilistic forecasting, optimization, and real-time control for smart reactive power management in future power grids. This position offers the opportunity to work at the intersection of power systems, control, optimization, and machine learning, with a strong focus on enhancing grid resilience and integrating renewable energy sources. The SPARC project is a collaborative initiative between TU/e (Eindhoven, Netherlands) and TUM (Munich, Germany), aiming to revolutionize reactive power management in modern power systems.

As a PhD candidate, you will develop probabilistic forecasting models for reactive power availability using machine learning and real-time data, design integrated optimization frameworks for ancillary service coordination considering grid constraints and market dynamics, and create real-time control architectures for seamless TSO-DSO interaction. Validation will be performed through Power Hardware-in-the-Loop (PHIL) simulations, and you will collaborate with grid operators such as Enexis to ensure practical relevance and impact. The position includes a six-month research stay at TUM to leverage complementary expertise and facilities, fostering cross-institutional collaboration.

The Department of Electrical Engineering at TU/e is renowned for its research in energy conversion, telecommunication, and electrical signal processing, with strong ties to high-tech industry and a commitment to addressing socially relevant issues. You will be part of a vibrant academic community, benefiting from high-quality training programs, technical infrastructure, and support for personal and professional growth. The university offers a green campus environment, excellent facilities, and a dynamic, international network.

Employment conditions include a four-year full-time contract, salary in accordance with the Collective Labour Agreement for Dutch Universities (scale P, €3,059–€3,881/month), year-end bonus, vacation pay, pension scheme, paid pregnancy and maternity leave, partially paid parental leave, commuting and home working allowances, and a tax compensation scheme for international candidates. You will spend at least 10% of your employment on teaching tasks, with opportunities to develop your teaching skills and coach students.

Applicants must hold a master’s degree in Electrical Energy Systems, Electrical Engineering, or Sustainable Energy Technology, with strong technical skills in power systems, control theory, optimization, or machine learning. Experience with programming (Python, MATLAB, or similar), data analysis, and power system simulation tools is desirable. Knowledge of stochastic optimization, real-time control, PHIL simulations, and lab experiments (Opal-RT/RTDS) is advantageous. Candidates should be fluent in English (C1 level), research-oriented, and able to work in interdisciplinary teams.

To apply, submit your application online via the provided link, including a cover letter, CV with publications, and contact information for three references. The vacancy will remain open until filled, with priority given to complete applications. Please note that applications sent by email or post will not be processed. For further information, contact Assistant Professor Niels Blaauwbroek at [email protected] or [email protected].