PhD Scholarships in Trustworthy Foundation Models and Physics-Informed Neural Networks for Power Systems - DTU Wind

Official occupation: ph.d., naturvidenskab og teknik. Employment conditions: Almindelige vilkår. Employer CVR: 30060946.

Primary career market

Public Sector, Education & Impact (employer-sector evidence). Are you a talented, self-motivated, and team-oriented person, who thrives in a collaborative environment and enjoys working with complex topics? We seek two PhD students willing to be part of a world leading research environment and contribute to the development for the next generation machine learning tools for power systems.

One PhD student will focus on physics-informed neural networks and their integration with large language models to accelerate power system dynamic simulations. The goal is to design methods that can seamlessly integrate large language models as orchestrators with physics-informed neural networks and commercial power system dynamic simulation tools.

The second PhD student will focus on the development of Trustworthy AI Foundation Models for or the secure operation and planning of real transmission and distribution grids. The Division for Power and Energy Systems of DTU Wind and Energy Systems provides cutting edge research in sustainable, reliable and cost-efficient energy systems to the benefit of society1 …