Master Thesis – Monitoring & AI for Geothermal and Energy Systems

Fraunhofer-Gesellschaft

Conducting research in AI for energy infrastructures and geothermal systems at Fraunhofer IEG. Engaging in real-world projects and collaborating with interdisciplinary teams.

Posted 6/19/2026full-timeBochum • 🇩🇪 GermanyMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Conducting literature reviews and evaluating state-of-the-art approaches in Machine Learning and Deep Learning
Performing data preprocessing, feature engineering, and exploratory data analysis on real-world datasets
Developing and implementing AI models, including neural networks, transformer architectures, and tree-based methods
Training, validating, and optimizing machine learning models through hyperparameter tuning and performance evaluation
Applying developed approaches to industrially relevant energy and geothermal use cases
Documenting research results and presenting findings within the project team

Requirements

What you’ll need

Enrollment in a Master's program at a German university in Engineering, Computer Science, Mathematics, Data Science, or a related STEM discipline
Knowledge of Machine Learning and Deep Learning methods
Experience with Python and common machine learning frameworks such as PyTorch, TensorFlow, or Scikit-Learn
Interest in data-driven research, predictive analytics, and AI applications for energy technologies
Strong analytical skills and a structured, independent way of working
High level of motivation and willingness to familiarize yourself with new scientific topics
Good communication skills and the ability to work collaboratively in an interdisciplinary research environment

Benefits

Comp & perks

Opportunity to contribute to cutting-edge research in the fields of Artificial Intelligence, Monitoring Technologies, Geothermal Energy, and Sustainable Energy Systems
Active involvement in real-world research projects addressing challenges of the energy transition
Close collaboration with experienced researchers and interdisciplinary teams
Freedom to contribute your own ideas and explore innovative AI approaches
Opportunity to conduct your Master’s thesis within an ongoing Fraunhofer research project
Access to modern tools, research infrastructure, and industry-relevant datasets
Flexible working hours and the possibility to work remotely within Germany
A collaborative and international research environment that encourages innovation, scientific curiosity, and continuous learning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Machine LearningDeep Learningdata preprocessingfeature engineeringexploratory data analysisAI modelsneural networkstransformer architecturestree-based methodshyperparameter tuning

Soft Skills

analytical skillsstructured workingindependent workingmotivationwillingness to learncommunication skillscollaborative work