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

Jobbeskrivelse

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

Your overall focus will be to advance the stability and reliability of renewable power systems through the development of machine learning-based control strategies. You will work closely with colleagues at DTU, our project partners from Siemens Gamesa, and other international collaborators in the NU-ACTIS project. The main purpose of this PhD position is to design, implement, and validate ML-assisted control solutions that can operate safely and effectively in inverter-dominated power systems, which is an increasingly critical challenge in the transition to renewable energy.

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?

• 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.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment

The assessment of the applicants will be based on the material submitted and one or two stages of interview, online and/or in person. During one of the two stages, the candidate might be asked to conduct paper review or another position related task.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. 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.

Further information

Further information may be obtained from Assistant Professor Johanna Vorwerk. 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

Your complete online application must be submitted no later than 20 February 2026 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• 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.