Master Thesis Electrical engineering (m/f/d)- Forschungszentrum Jülich GmbH

Conducting research for a changing society: This is what drives us at Forschungszentrum Jülich. As a member of the Helmholtz Association, we aim to tackle the grand societal challenges of our time and conduct research into the possibilities of a digitized society, a climate‑friendly energy system, and a resource‑efficient economy. Work together with around 7,600 employees in one of Europe’s biggest research centres and help us to shape change! At the Institute of Energy and Climate Research – Jülich Systems Analysis (ICE‑2), the ICE‑2 team “Integrated Infrastructure – Distribution Infrastructure” develops synthetic, geo‑referenced distribution grids for electricity, gas, and hydrogen. These efforts support the planning of robust, climate‑neutral infrastructure systems by analysing load profiles, technology placement, and sector integration. By joining us, you’ll contribute to Germany’s energy transition and digital transformation through cutting‑edge research.

Activities and responsibilities

• Researching and extracting industrial and commercial buildings across Germany using open‑source geospatial data (e.g., OpenStreetMap, CORINE Land Cover, Sentinel, etc.)
• Applying machine learning / AI and/or statistical algorithms to classify building and land‑use types relevant to electrical consumption
• Labeling and preparing training data for AI models; developing automated pipelines for classification
• Integrating findings into the existing synthetic grid package for generating realistic medium‑voltage distribution grids
• Collaborating with domain experts from energy modelling, geoinformatics, and data science
• Preparing scientific documentation of your methodology and results
• Contributing to writing scientific papers for internal reporting and possible publication

Required qualifications

• Very good performance in master’s studies in electrical engineering, computer science, geoinformatics, energy systems, or a related field
• Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit‑learn, TensorFlow, and PyTorch)
• Experience in working with geospatial data (e.g., GeoPandas, Rasterio, and Shapely)
• Interest in AI and energy systems modelling
• Ability to communicate and document research results clearly in English (B2)

Desirable qualifications

• GIS experience (QGIS, GDAL), basic understanding of distribution grid concepts and tools like PyPSA
• Experience with academic writing or contributions to scientific papers
• High level of independence, motivation, and a structured, reliable work approach
• Good team skills and willingness to engage in interdisciplinary collaboration
• We welcome applications even if you do not have all the required and desirable skills and knowledge

Benefits

• Meaningful tasks: Your thesis deals with a future‑oriented, socially relevant topic with direct practical relevance in an international environment
• Practical relevance: You will gain valuable practical experience alongside your studies and actively participate in interdisciplinary projects
• Scientific environment: You can expect excellent scientific equipment, modern technologies, and qualified support from experienced colleagues
• Onboarding and teamwork: You will have structured training for your tasks and support from the beginning, including Welcome Days and a Welcome Guide (
• Work‑life balance: Flexible working hours, possibility of 100% home office, and flexible location options
• Fair remuneration: Reasonable remuneration for your thesis
• Fixed term: The position is initially for a fixed term of six months

This job will remain open until the position has been successfully filled. Please apply via the online recruitment system:

We welcome applications from people with diverse backgrounds, including age, gender, disability, personal orientation, and social, ethnic, and religious origin. We are committed to an inclusive working environment with equal opportunities for all.

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