Publisher
source

Technical University of Denmark

PhD scholarship

PhD Scholarships in Trustworthy Foundation Models and Physics-Informed Neural Networks for Power Systems Technical University of Denmark in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

PhD scholarships at DTU; full-time positions under the collective agreement with the Danish Confederation of Professional Associations. Salary follows DTU scientific staff salary structure. No stipend amount is stated. The positions are part of funded European projects (GENAISIS and AI4Power).

Deadline

Oct 15, 2026

Country flag

Country

Denmark

University

Technical University of Denmark

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Keywords

Computer Science
Data Science
Electrical Engineering
Mathematics
Power Dynamics
Statistics
Power System
Physics
Large Language Models
Renewable Energy Systems
ML

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About this position

DTU Wind and Energy Systems at the Technical University of Denmark is advertising two PhD scholarships in trustworthy foundation models, physics-informed neural networks, and power systems. The positions sit at the intersection of machine learning, data science, power system simulation, and energy systems, with one project focused on integrating physics-informed neural networks with large language models for faster dynamic simulations, and the other focused on trustworthy AI foundation models for secure operation and planning of transmission and distribution grids.

The PhD students will join the Division for Power and Energy Systems within DTU Wind and Energy Systems, a large and internationally active research environment. The work is embedded in major European projects: GENAISIS and the Marie-Curie Doctoral Network AI4Power. These projects emphasize trustworthy AI, explainability, adaptability, and large-scale energy-system applications across multiple countries and industrial/academic partners.

Applicants should hold a two-year master's degree (120 ECTS) or equivalent in engineering, mathematics, computer science, computer engineering, physics, sustainable energy, or a related field. Strong preparation in machine learning, statistics, numerical methods, power system dynamics/optimization, and programming (Python, Julia, PyTorch, etc.) is desirable, along with familiarity with tools such as PowerFactory, PSCAD, or EMTP. Excellent English and the ability to present and publish research are also expected.

The positions are full-time PhD scholarships under DTU salary and appointment terms. The post does not state a specific stipend amount. The application deadline is 15 October 2026, and applications are reviewed on an ongoing basis before the deadline.

To apply, submit the online application as one PDF in English including a cover letter, CV, transcripts, diploma, a research statement (max 700 words), and contact details for two referees. Applicants should indicate which of the two PhD projects they prefer. The position is based in Kgs. Lyngby, Denmark.

Funding details

PhD scholarships at DTU; full-time positions under the collective agreement with the Danish Confederation of Professional Associations. Salary follows DTU scientific staff salary structure. No stipend amount is stated. The positions are part of funded European projects (GENAISIS and AI4Power).

What's required

Applicants must have a two-year master's degree (120 ECTS) or an equivalent academic degree. Suitable backgrounds include engineering, mathematics, computer science, computer engineering, physics, sustainable energy, or related disciplines. Candidates should have a solid background in four or more of the following: machine learning, statistics and probabilities, numerical methods for time-domain simulations, power system dynamics, power system optimization, programming in Python/Julia/PyTorch, power system software such as PowerFactory, PSCAD, or EMTP, excellent English, and the ability to present results and write scientific papers. Self-motivation, teamwork, and interest in complex topics are emphasized.

How to apply

Apply online through the DTU application portal using the Apply now link. Submit one PDF in English containing a cover letter, CV, transcripts and BSc/MSc diploma with grading scale, a research statement (max 700 words), and contact details for two referees. Indicate which of the two PhD projects you are applying for. Incomplete or late applications will not be considered.

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