PhD scholarship in Trustworthy AI for control of Renewable Power Grids – DTU Wind

Do you want to work on real-world challenges at the intersection of machine learning and power system stability? We are looking for a PhD student with a background in control engineering, machine learning, or power systems to join the international research project NU-ACTIS. In this role, you will help develop reliable and explainable machine learning (ML) based control strategies for power systems with a high share of inverter-based resources. The position offers the opportunity to work on practical solutions to emerging stability problems in the Nordic countries, collaborate with leading academic and industrial partners, and gain experience with advanced simulation tools and regulatory frameworks, while contributing to the safe and efficient integration of renewable energy into the grid.

Responsibilities and qualifications

Specifically, the aim of this position is to explore how ML can be used to design control strategies that are not only high performing under uncertainty but also explainable and verifiable. You will contribute to the development of methods for assessing the safety and robustness of these controllers and help integrate them into commercial simulation tools used by industry. The project will be carried out in close collaboration with Siemens Gamesa and other NU-ACTIS partners, ensuring that your research is aligned with both academic and industrial needs.  Key research questions may include: How can ML-based controllers be designed to meet strict safety and performance requirements? What are the most effective ways to verify their behaviour under uncertainty? And how can these solutions be made trustworthy and transparent enough for use in critical infrastructure? 

Your primary tasks will be to:

• Design and compare ML-based control strategies for inverter-dominated power systems
• Integrate ML controllers into dynamic simulation environments
• Develop methods for verifying safety and performance of ML-based control
• Participate in testing and validation using power system models developed by project partners
• Contribute to publications, workshops, conferences and open-source tools

We welcome applicants who are motivated to contribute to the future of renewable energy and power system stability through machine learning and control engineering. You are not expected to tick every box, but you should be excited about working across disciplines and tackling complex technical challenges. Ideally, you bring experience in at least three of the following areas:

• Classic power system dynamics and stability
• Control systems 
• Machine learning and artificial intelligence
• Power system modelling and dynamic simulation
• Programming (e.g., Python, MATLAB)
• Dynamics of renewable power systems and inverter-based technologies

We also value strong communication and collaboration skills, curiosity, and the ability to work independently in a multidisciplinary research environment. If you are unsure whether your background fits perfectly, we still encourage you to apply since your unique perspective might be exactly what we are looking for.

You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.

Approval and Enrolment

We offer

Salary and appointment terms

Starting date is 1 June 2026 (or according to mutual agreement), but no later than 1 July 2026. The position is a full-time position.

You can read more about career paths at DTU here .

Further information

You can read more about DTU Wind and Energy Systems at www.wind.dtu.dk 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. 

Application procedure 

one PDF file

• A letter motivating the application (cover letter)
• Curriculum vitae 
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
• A Research Statement (max. 700 words) where you outline a potential research direction that interests you. The research statement shall address the following three questions: (1) What – what is the topic you propose to research? (2) Why – why is it necessary to develop a solution (or a new solution, if one already exists) for this topic? (3) How – how do you plan to develop a solution for this topic (general research directions, not necessary to go into too much detail). The research topic you discuss is entirely up to you; it may or may not be related to the research topic of the position advertised.
• Contact details of two individuals who can provide a reference upon request.

You may apply prior to ob­tai­ning your master’s degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

The Department of Wind and Energy Systems

Technology for people

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