About the opportunity
The Division for Power and Energy Systems of DTU Wind and Energy Systems invites applications for two fully funded PhD scholarships. One PhD student will focus on physics-informed neural networks and their integration with large language models to accelerate power system dynamic simulations. The second PhD student will focus on developing Trustworthy AI Foundation Models for the secure operation and planning of real transmission and distribution grids. These positions are part of the European Project GENAISIS and the Marie-Curie Doctoral Network AI4Power, providing a collaborative research environment with international partners across Europe.
Salary and benefits
- Salary and appointment terms based on the collective agreement with the Danish Confederation of Professional Associations
- Participation in international research projects and collaboration with industry
- Opportunities to assist in teaching courses and co-supervise BSc and MSc students
- Dynamic working environment with an international staff and a team-oriented atmosphere
Who can apply?
- Two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree
- Background in engineering, mathematics, computer science, computer engineering, physics, sustainable energy, or any related discipline
- Solid background in four or more areas including machine learning techniques, numerical methods for time-domain simulations, power system dynamics, power system optimization, programming tools (Python, Julia, PyTorch), and power system software (Powerfactory, PSCAD, EMTP)
- Excellent command of the English language and ability to prepare scientific papers for international journals
Required documents
- 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) addressing what, why, and how regarding a potential research direction
- Contact details of two individuals that can provide a letter of reference
When to apply
- Application deadline is 15 October 2026 (23:59 Danish time)
- Assessment of applications is ongoing and starts before the application deadline
How to apply
- Prepare all required application materials in English and merge them into one PDF file
- Open the online application link and fill out the online application form
- Upload the single PDF file containing your documents and submit before the deadline
Additional information
- Desired starting date is 1 November 2026 or flexible by mutual agreement
- Applicants may apply prior to obtaining their master's degree but cannot begin before receiving it
- Open-source background checks may be conducted on qualified candidates due to critical technology research rules
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- Hold a two-year Master's degree in Engineering, Computer Science, or Physics.
- Possess a strong background in machine learning, numerical methods, and power system dynamics.
- Proficient in Python, Julia, or PyTorch.
What should you think carefully about?
- The role requires a very specific intersection of skills in machine learning and power system software (e.g., Powerfactory, PSCAD), which may not all be found in one candidate.
- Relocation to Kgs. Lyngby, Denmark, will be necessary as the role is on-site.
- Qualified candidates may be subject to open-source background checks due to the nature of the critical technology research.
How could this fit your current goals and plans?
This is an ideal opportunity for someone looking to launch a high-impact PhD career within a collaborative European network (GENAISIS and AI4Power), gaining experience in both academic research and industry collaboration.
Our take
Highly recommended for Master's graduates in AI and Power Systems who want to lead cutting-edge research in trustworthy AI for critical infrastructure.
Ready to apply?
Review the opportunity on the official website before applying.
Official-source verified
