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Breadcrumb Home Working at Job opportunities Postdoc Position: Uncertainty Quantification for Power Systems Postdoc Position: Uncertainty Quantification for Power Systems Employment 0.95 - 1.0 FTE Gross monthly salary € 3,706 - € 5,760 Required background PhD Organizational unit Faculty of Science Application deadline 27 November 2026 Apply now How do we keep a power grid stable when it runs on wind, sun and power electronics? And how far can we trust our simulations when so much about the future grid is uncertain? Answering these questions requires advanced numerical methods for modelling and simulating complex power systems. As a postdoc in the NWO-funded UTOPYS programme, you will help make a new real-time electromagnetic transient (EMT) simulator a reliable tool for research. Join a consortium of eight leading Dutch institutions, contribute to groundbreaking research and help shape the future of energy. We are looking for a postdoctoral researcher with a background in scientific computing to contribute to the development of computational methods for large-scale power system simulation. You will become a member of the Department of Mathematics at Radboud University (Nijmegen, Netherlands) and join the research group of Gabriel Lord and Laura Scarabosio, as part of UTOPYS (Understanding Large, Complex Power Systems). UTOPYS is a ten-year programme to build a new theory of large, complex power systems, enabled by a state-of-the-art real-time power system simulator. As renewables and power electronics come to dominate the grid, we face unexplained blackouts, wide-area oscillations and converter-driven instabilities that traditional theory cannot fully explain. To study them, UTOPYS is building a state-of-the-art real-time EMT simulation facility at TU Delft. A facility like this is only as valuable as the models that run on it, and those models depend on uncertain parameters, operating conditions and scenarios. Radboud’s contribution is to develop the uncertainty quantification methodology that makes simulation results on this infrastructure reliable and interpretable. As a postdoc, you will develop and implement advanced methods for uncertainty quantification on the UTOPYS facility. This includes model reduction and system identification, for example deriving equivalent models of parts of the network and estimating parameters and topology changes from day-to-day measurements such as PMU data. You will also develop methods to generate realistic parameter families, so that large models can be populated with plausible, varied components rather than identical defaults. Together with the other UTOPYS postdocs, you will take part in regular joint sessions at TU Delft, where you will learn to work with the real-time EMT simulator and help build the shared transmission model. You will also participate in relevant conferences and workshops and publish your findings in peer-reviewed journals. I try to help budding academics feel just as at home at Radboud University as I do. Laura van Niftrik Professor of Microbiology at the Faculty of Science Laura van Niftrik is a Professor of Microbiology at the Faculty of Science. "Strong collegiality is one of the unique characteristics of Radboud University. There is a safe, friendly atmosphere. It’s easy to collaborate with colleagues from other research groups and faculties, and I have never seen any kind of competitiveness between my co-workers. The university still has some way to go when it comes to diversity, whether we’re talking about gender, culture or ethnicity. At the same time, I’m glad to see that a great deal of attention is being paid to this issue. This is evident in such practices as mentorship, which is something from which I’ve also benefited during my academic career. Spending time with an experienced academic so that you can brainstorm and bring each other up to speed on things can be quite helpful. Now that I’m a professor myself, I’ve also taken on the role of mentor. This has allowed me to help budding academics to feel just as at home at Radboud University as I do." Does this sound like you? You hold, or are working towards, a PhD degree in Applied Mathematics, Electrical Engineering or related (to be completed before the start date). You have a strong background in scientific computing and numerical analysis, and you possess software development skills (e.g., Python). Knowledge of uncertainty quantification or power systems is a plus. You are a team player who enjoys working in a dynamic, interdisciplinary team. You have good verbal and written communication skills. You can manage complex projects to completion on schedule. What we offer you We will give you a temporary employment contract of two years. Your salary within salary scale 10 depends on your previous education and number of years of (relevant) work experience. The amounts in the scale are based on a 38-hour working week. You will receive an 8% holiday allowance and an 8,3% end-of-year bonus. You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20. Additional employment conditions Work and science require good employment practices. Radboud University's primary and secondary employment conditions reflect this. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself. For example, exchange income for extra leave days and receive a reimbursement for your sports membership. In addition, you receive a 34% discount on the sports and cultural activities at Radboud University as an employee. And, of course, we offer a good pension plan. We also give you plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes. Where you will be working The position is part of the Applied Mathematics research group within the Department of Mathematics at Radboud University. Research within the group is represented by Riccardo Cristoferi, Gabriel Lord, Vanja Nikolić, Laura Scarabosio, and Stefanie Sonner. The Department of Mathematics covers a broad range of topics in pure and applied mathematics, with strong interdisciplinary links and active collaborations with industry. It has a friendly and welcoming atmosphere, with a healthy balance between senior and early-career staff from around the world, and a community of more than 20 PhD candidates. There are regular research seminars as well as a number of informal events throughout the year. The Department of Mathematics is part of the Institute for Mathematics, Astrophysics and Particle Physics within the Faculty of Science. Several activities are organised jointly across the institute to foster interdisciplinary interaction. Faculty of Science The Faculty of Science (FNWI), part of Radboud University, engages in groundbreaking research and excellent education. In doing so, we push the boundaries of scientific knowledge and pass that knowledge on to the next generation. We seek solutions to major societal challenges, such as cybercrime and climate change and work on major scientific challenges, such as those in the quantum world. At the same time, we prepare our students for careers both within and outside the scientific field. Currently, more than 1,300 colleagues contribute to research and education, some as researchers and lecturers, others as technical and administrative support officers. The faculty has a strong international character with staff from more than 70 countries. Together, we work in an informal, accessible and welcoming environment, with attention and space for personal and professional development for all. Radboud University At Radboud University, we aim to make an impact through our work. We achieve this by conducting groundbreaking research, providing high-quality education, offering excellent support, and fostering collaborations within and outside the university. In doing so, we contribute indispensably to a healthy, free world with equal opportunities for all. To accomplish this, we need even more colleagues who, based on their expertise, are willing to search for answers. We advocate for an inclusive community and welcome employees with diverse backgrounds, cultures, and perspectives. If you want to learn more about working at Radboud University, follow our Instagram account (link is external) and read stories from our colleagues. Is this the job for you? You can apply only via the button below. Address your letter of application to Gabriel Lord. In the application form, you will find which documents you need to include with your application. We look forward to receiving your application. The first interviews will take place on Tuesday 15 December and Wednesday 16 December. You will preferably start your employment as soon as possible. We can imagine you're curious about our application procedure. It describes what you can expect during the application procedure and how we handle your personal data and internal and external candidates. Do you already work at Radboud University and have questions about making an internal move? Learn more about internal applications. Apply now Application deadline 27 November 2026 We would like to recruit our new colleague ourselves. Acquisition in response to this vacancy will not be appreciated. Want to know more about this position? Prof. G.J. Lord (Gabriel) Dr L. Scarabosio (Laura) Last modified: 28 October 2026 Share this page

Core Responsibilities

Develop and implement uncertainty quantification methods for large-scale power system simulations, including model reduction, system identification, and methods for generating realistic parameter families. Collaborate with the UTOPYS consortium to use the real-time EMT simulator, contribute to a shared transmission model, and publish research findings.

Requirements

Applicants must hold or be completing a PhD in Applied Mathematics, Electrical Engineering, or a related field before the start date, and have a strong background in scientific computing and numerical analysis. Software development skills such as Python, strong communication and teamwork, and the ability to complete complex projects on schedule are required; knowledge of uncertainty quantification or power systems is an advantage.

Benefits

• Holiday Allowance
• End-of-Year Bonus
• Additional Annual Leave
• Flexible Working Hours
• Leave Arrangements
• Work From Home
• Sports Membership Reimbursement
• Discounted Sports and Cultural Activities
• Pension Plan
• Training and Development Opportunities