Peter Palensky

This PhD project at Delft University of Technology focuses on energy data sharing for city-level policy making using digital twins within the FEDERATE NWO project. The research addresses a practical bottleneck in municipal decarbonization and sustainability planning: digital twins often depend on fragmented, partial, and incomplete data, while municipalities need richer and more actionable information to support policy decisions. The doctoral researcher will study data sharing architectures that can connect citizens, local companies, and municipalities in ways that are compatible with the digital twins used by cities. A central part of the work is the design of ontologies and knowledge graphs , together with their integration into municipal digital twin environments and related tools for gathering data from citizens and companies. The position is embedded in the Faculty of Electrical Engineering, Mathematics and Computer Science , in the Intelligent Electrical Power Grids section of the Department of Electrical Sustainable Energy. The group is led by Prof. Peter Palensky and works on advanced power technologies and intelligent control approaches for reliable, efficient, stable, affordable, and sustainable energy systems. The department also offers a strong research environment with extensive infrastructure, including high-voltage laboratories, DC grid testing environments, and large-scale RTDS simulation capabilities. The project emphasizes both scientific rigor and near-term application potential, with opportunities to collaborate with industrial partners and researchers from other disciplines. The team also strongly supports open science through publishing, source code, and data sharing. The PhD candidate will contribute to scientific publications, project deliverables, project meetings, and teaching-related activities within the subject area. The project is supervised by Dr. Milos Cvetkovic .

The Delft University of Technology invites applications for a four-year PhD position focused on "Foundation AI models for distribution systems decision-making." Foundation models represent a cutting-edge learning paradigm in artificial intelligence, capable of generalizing across diverse applications by leveraging large datasets and self-supervision. While commercial large language models (LLMs) are prominent examples, foundation models are increasingly applied to time-series, audio, and video data. Their potential in power systems is recognized, particularly for tasks such as power flow calculations, congestion management, and voltage control, all within a unified architecture that can learn from multimodal data sources. This doctoral project aims to address key scientific challenges, including integrating power systems physics into AI model architectures and developing architectures invariant to distribution system topology. The research will be conducted within the Intelligent Electrical Power Grids (IEPG) section of the Faculty of Electrical Engineering, Mathematics, and Computer Science. The IEPG group, led by Prof. Peter Palensky, is dedicated to advancing the reliability, efficiency, and sustainability of electrical power systems through innovative technologies and smart controls. Supervision will be provided by Dr. Pedro P. Vergara (Associate Professor) and Prof. Peter Palensky (Chair IEPG), offering guidance in both technical and interdisciplinary aspects. The project encourages collaboration with industrial partners and academics from related fields such as mathematics and operations research. The team values mathematically rigorous methods and open science, including publishing, source code, and data sharing. The PhD candidate will also participate in teaching activities, including student supervision and laboratory work. The Department of Electrical Sustainable Energy (ESE) at TU Delft is renowned for its research in DC systems, energy conversion and storage, photovoltaic materials and devices, high voltage technologies, and intelligent electrical power grids. The department boasts advanced laboratory facilities, including high voltage testing and real-time simulation environments for future power systems. Applicants should possess basic knowledge of power systems and machine learning/AI, hold an MSc degree in a technical discipline (e.g., computer science, electrical engineering), and demonstrate excellent analytical skills. English proficiency is required, with a minimum TOEFL score of 100 or IELTS 7.0 per sub-skill. Desirable skills include experience with optimization methods, scheduling problems, Python programming, and familiarity with tools such as Pyomo and version control systems. Employment is offered for four years, initially as a 1.5-year contract with a progress assessment, followed by a 2.5-year extension upon satisfactory performance. The salary ranges from €3059 to €3881 gross per month, plus holiday and end-of-year bonuses. Additional benefits include health insurance discounts, flexible work schedules, and support for relocation to the Netherlands. The TU Delft Graduate School provides a stimulating research environment and professional development opportunities. To apply, submit your CV, motivational letter, and a list of grades for your qualifying degrees via the online application portal by 1 August 2026. Applications sent by email or post will not be processed. For further information, consult the TU Delft PhD admission requirements and departmental websites.