Master Thesis - Physics-Informed Machine Learning for Dynamic Power System
Characterization
Master Thesis - Physics-Informed Machine Learning for Dynamic Power System
Characterization
At the Institute of Climate and Energy Systems Engineering (ICE-1) we focus
on the development of models and algorithms for simulation and optimization of
decentralized, integrated energy systems. Such systems are characterized by
high shares of renewable energies and increasing sector coupling, which leads
to high spatial and temporal variability of energy supply and demand as well
as a high degree of interdependence of material and energy flows. Our research
at the ICE institute aims to provide scalable and faster-than-real-time
capable methods and tools that enable the energy-optimal, cost-efficient and
safe design and operation of future energy systems.
Your Job
The transition toward renewable and converter-interfaced energy resources is
creating increasingly fast and complex dynamics in modern power systems. In
this Master's thesis, you will develop a physics-informed digital-twinning
approach to better characterize these dynamics and estimate relevant
electrical and control parameters from transient voltage and current data.
Your tasks will include:
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
Your Profile
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
Our Benefits for You
We work on the very latest issues that impact our society and are offering you
the chance to actively help in shaping the change! We offer ideal conditions
for you to complete your studies:
Meaningful Tasks: Your thesis deals with a future-oriented, socially
relevant topic with direct practical relevance in an international
environment
Practical relevance: With us, you will gain valuable practical
experience alongside your studies and actively participate in
interdisciplinary projects, , including project meetings and, where
appropriate, conferences.
Scientific environment: You can expect excellent scientific equipment,
modern technologies, and qualified support from experienced colleagues
Personal responsibility: You organize your tasks independently - from
preparation to implementation
Onboarding & teamwork: You can look forward to working in a dedicated,
international, and collegial team. It is important to us that you quickly
settle into the team and are given structured training for your tasks. We
also support you from the very beginning and make your start easier with
our Welcome Days and Welcome Guide
Work-life balance: We offer flexible working hours to help you balance
your professional and personal life. You also have the option of flexible
working (in terms of location), which is generally possible after
consultation and in line with upcoming tasks and (on-site) appointments
Flexibility: Flexible working hours make it easier for you to balance
work and study
Campus experience: Our research campus in the countryside creates
ideal conditions for collegial exchange and sporting activities right on
site. Our cafeteria offers a wide range of options—you can enjoy a
relaxing lunch break with a lake view
Perspective: We provide strong support and mentoring to help you
prepare for a future career in science or industry. If you have the
appropriate qualifications and funding is available, the institute also
offers the opportunity to pursue a PhD after completing your master's
thesis
Fair remuneration: We will pay you a reasonable remuneration for your
thesis
In addition to exciting tasks and a collegial working environment, we offer
you much more: https: // go.fzj.de/benefits
We welcome applications from people with diverse backgrounds, e.g. in terms of
age, gender, disability, sexual orientation / identity, and social, ethnic and
religious origin. A diverse and inclusive working environment with equal
opportunities in which everyone can realize their potential is important to
us.
The following links provide further information on diversity and equal
opportunities: https: // go.fzj.de/equality and on specific support options for
women: https: // go.fzj.de/womens-job-journey
Place of Employment: Jülich
Start Date: To the next possible date
Salary: We will pay you a appropriate remunerationfor your thesis
Application Deadline: The position will be published until it is
successfully filled
Index number: 2026M-0692
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