Master Thesis - Physics-Informed Machine Learning for Dynamic Power System Characterization

Salary: 47.000 - 87.000 € per year

Requirements:

Excellent university degree (Bachelor) in field of Data Science or a comparable field i.e. Electrical Engineering, Computer Science/ Engineering, Physics or the like

Strong mathematical background

Interest in energy systems, power grids and their components

Excellent knowledge and experience in programming Python

Excellent knowledge and experience in machine learning

Excellent ability for cooperative collaboration

Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR), ideally supported by a certificate confirming the language level

Knowledge of the German language is not mandatory but certainly appreciated

Responsibilities:

Developing and analyzing representative dynamic simulation scenarios for electrical power systems

Extending kernel-based Gaussian Process methods for the estimation of electrical and control parameters

Integrating physical knowledge, such as governing differential equations and physical constraints, into probabilistic kernel models

Developing and evaluating a physics-informed digital-twinning methodology based on known system parameters and reference simulations

Assessing the approach with regard to estimation accuracy, uncertainty quantification, numerical robustness, and computational efficiency

Analyzing and documenting your results and deriving conclusions for the applicability of the developed approach

Technologies:

Support

Machine Learning

Python

More:

Place of employment: Jülich. Start date: To the next possible date. We offer appropriate remuneration for your thesis and publish the position until it is successfully filled. The role focuses on a Masters thesis on a physics-informed digital-twinning approach for modern power systems in an international environment. We offer meaningful tasks with practical relevance, excellent scientific equipment, modern technologies, qualified support from experienced colleagues, flexible working hours, flexible working options after consultation, a dedicated international and collegial team, structured onboarding through our Welcome Days and Welcome Guide, strong support and mentoring for future careers in science or industry, and the possibility of a PhD after the masters thesis if qualifications and funding are available. We also provide a campus environment with collegial exchange, sporting activities, and a cafeteria with a lake view, and we value diversity, inclusion, and equal opportunities.

last updated 37 week of 2026