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Forschungszentrum Jülich

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Master Thesis in Physics-Informed Machine Learning for Dynamic Power System Characterization Forschungszentrum Jülich GmbH in Germany

Degree Level

Master's

Field of study

Computer Science

Funding

The thesis is paid with appropriate remuneration. The post also mentions that, if suitable qualifications and funding are available, there may be an opportunity to pursue a PhD after the master’s thesis.

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Country

Germany

University

Forschungszentrum Jülich

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Keywords

Computer Science
Electrical Engineering
Mathematics
Digital Twin Technology
Gaussian Processes
Statistics
Power System
Physics
Renewable Energy Systems
ML

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About this position

Master Thesis opportunity at Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems Engineering (ICE-1), in Jülich, Germany.

The project is titled Physics-Informed Machine Learning for Dynamic Power System Characterization and focuses on power systems, electrical engineering, machine learning, Gaussian Processes, digital twins, and physics-informed modeling. The thesis aims to develop a physics-informed digital-twinning approach to characterize fast dynamics in modern power systems and estimate electrical and control parameters from transient voltage and current data.

Typical tasks include building dynamic simulation scenarios, extending kernel-based Gaussian Process methods, integrating physical constraints and differential equations into probabilistic models, evaluating estimation accuracy and uncertainty quantification, and documenting the results.

Eligibility highlights: an excellent bachelor’s degree in Data Science or a related field such as Electrical Engineering, Computer Science/Engineering, or Physics; strong mathematical background; interest in energy systems and power grids; excellent Python and machine learning skills; and English at least B2 level. German is not required.

Funding: the thesis is paid with appropriate remuneration. The posting also notes a possible pathway to a PhD after the master’s thesis if qualifications and funding are available.

Application: submit via the online application portal. The position is open until filled, so early application is advisable.

Funding details

The thesis is paid with appropriate remuneration. The post also mentions that, if suitable qualifications and funding are available, there may be an opportunity to pursue a PhD after the master’s thesis.

What's required

Applicants should have an excellent bachelor’s degree in Data Science or a comparable field such as Electrical Engineering, Computer Science/Engineering, Physics, or similar. A strong mathematical background is required, along with interest in energy systems, power grids, and their components. Excellent Python programming skills, strong machine learning experience, and very good written and spoken English at least at B2 CEFR level are required; German is not mandatory but is appreciated. Cooperative collaboration skills are also expected.

How to apply

Apply through the online application portal linked in the posting. Review the application information and FAQ pages before submitting. For questions, use the provided contact form or career portal.

More information can be found here

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