PhD scholarship in AI Solutions for Renewable Power System Stability Assessment - DTU Wind
Kgs. Lyngby, Denmark
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DTU - Technical University of Denmark
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet.Are you passionate about renewable energy and eager to apply machine learning to real-world challenges?
Join our research team at DTU and work on groundbreaking advancements in renewable power system dynamics. Collaborate with experts from DTU and IIT Bombay, gain hands-on experience with advanced simulation tools, and contribute to high-impact publications. Enhance your professional network through international research stays and develop innovative solutions that support the global transition to sustainable energy systems. Apply now to make a difference in the field of renewable energy.
Responsibilities and qualifications
Your overall focus will be to advance the field of renewable power system dynamics through innovative machine learning solutions. You will work closely with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models for dynamic simulations of renewable power systems, addressing critical challenges in stability and dynamics.
Specifically, the aim of this position is to develop comprehensive guidelines for verifying and testing dynamic equivalencing methods for power system dynamic simulations and integrating these into commercial simulation tools. Dynamic equivalents are simplified representations of complex power system components or areas that retain the essential dynamic characteristics of the original system. They are crucial for renewable power systems as they significantly reduce the complexity of simulations while ensuring accurate and efficient analysis of system behavior under various conditions. Dynamic equivalents enable faster and potentially more reliable stability assessments, which are vital for integrating renewable energy sources into the power grid. Key research questions may include: How can machine learning be leveraged to improve the accuracy and speed of dynamic simulations in renewable power systems? What are the most effective methods for developing and validating dynamic equivalents for various simulation domains? How can these equivalents be integrated into existing simulation tools?
Your primary tasks will be to:
- Develop and implement machine learning models for dynamic simulations of renewable power systems
- Develop comprehensive guidelines for verifying and testing dynamic equivalents
- Integrate dynamic equivalents into commercial simulation tools
- Conduct high-quality research and publish findings in top-tier journals and conferences
- Collaborate with international research teams and participate in joint projects
- Co-supervise BSc and MSc student projects and contribute to the teaching at our institute
- Present research results at international conferences and workshops
- Engage in knowledge transfer activities with industry partners
Besides a passion for renewable energy and sustainability, a successful candidate will fulfill at least 3 points in the following list of qualifications:
- A strong background in machine learning and artificial intelligence
- Experience with numerical analysis and scientific computing
- Knowledge of power systems and renewable energy technologies
- Experience in power system simulation and modelling tools
In addition, we look for a candidate with strong communication and collaboration abilities as well as excellent problem-solving and analytical skills that have been demonstrated through previous research projects, i.e. an internship of a master thesis.
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
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 candidates will be based on the material they submit and one or two stages of interview, online and/or in person. During one of the two stages, the candidates will be asked to review a paper sent to them, describing its strengths, weaknesses, and potential for future extensions.
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 September 2025 (or according to mutual agreement). The position is a full-time position.
You can read more about career paths at DTU here.
Further information
Further information may be obtained from Johanna Vorwerk, Assistant Professor at DTU Wind and Energy Systems, vorjo@dtu.dk.
You can read more about DTU Wind 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 29 July 2025 (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.
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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