Postdoc Trustworthy AI-driven Grid Analytics for Congestion Forecast Applications

Postdoc Trustworthy AI-driven Grid Analytics for Congestion Forecast Applications

Advance trustworthy grid analytics by developing validation frameworks and datasets that quantify power grid data quality and support robust AI-based methods.

Job description

As a postdoctoral researcher, you will contribute to the project GridData – Metrology for reliable power grid data analytics, a European metrology project aimed at enabling safe and reliable operation of electricity grids in an era of high renewable energy penetration and increasing system complexity.

Your role will focus on the validation and benchmarking of data analysis methods used for grid monitoring and forecasting, especially under scenarios with high uncertainty, abnormal phenomena, or incomplete data. You will collaborate with a multi-partner consortium across Europe to deliver a framework that quantifies data quality, integrates measurement uncertainty, and provides reference datasets based on real and simulated data.

By helping define and evaluate metrologically sound methodologies for assessing the performance and reliability of algorithms—including AI-based approaches—you will support the grid operators, measurement supply chains, and standards organisations in adopting data-driven decision support tools. Your contribution will ensure these tools meet the requirements of the EU AI Act for high-risk systems like energy infrastructure.

You will co-develop synthetic datasets using digital twins and support the application of the framework to real-time event detection and forecasting of grid congestion and imbalance. The work will involve close collaboration with both research institutes and industry stakeholders. Your results will contribute to new best practices and standardisation efforts within European committees.

You will work with Dr. Simon Tindemans and a team of researchers working on flexible, risk-aware energy systems. You will be a member of the Intelligent Electrical Power Grids (IEPG) Section of the Electrical Sustainable Energy (ESE) Department, which is part of the Electrical Engineering, Mathematics, and Computer Science (EEMCS) Faculty.

Job requirements

• PhD in Electrical Engineering, Applied Mathematics, or a related field, with a focus on power systems, forecasting, or metrology.
• Demonstrated experience with probabilistic forecasting, grid congestion modeling, or data-driven decision support, particularly in operational environments.
• Proven experience working with real-world grid datasets, feature engineering, and uncertainty quantification in AI-based models.
• Knowledge of DSO processes and grid operator needs, ideally from prior applied research or industrial collaboration.
• Proficiency in Python or similar for model development, validation, and integration with hardware-in-the-loop testing environments.
• Strong scientific writing and communication skills in English.

Nice to haves:

• Familiarity with real-time digital simulators (RTDS), RSCAD, or similar platforms.
• Experience with validation frameworks, metrological uncertainty, or standardisation in a data science context.
• Prior collaboration with Dutch or European grid operators, or familiarity with energy policy and regulatory frameworks (e.g. EU AI Act).
• Proficiency in Dutch is a plus for stakeholder engagement.
• Active participation in open-source software, dataset publication, or reproducible research practices.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Dr. Simon Tindemans, via s.h.tindemans@tudelft.nl.