With more than 120 employees, the Institute of Solar Research conducts research into a sustainable and CO2-free energy supply from solar energy. Our research focuses on concentrating solar technologies that convert sunlight into heat, electricity and fuels. We also conduct research in related areas: We use sensor technology and data analysis to evaluate the energy efficiency of buildings and develop refurbishment strategies. We develop systems for solar power plants and photovoltaic systems to measure and predict solar radiation data. Other important areas of Research include the quality assurance of solar thermal power plants and photovoltaic systems and the decarbonisation of the chemical industry.
What to expect
We are offering an exciting opportunity to contribute to the final stages of a groundbreaking methodology that integrates AI-driven reflectivity predictions with real-time digital twin technologies for heliostat fields. This project plays a crucial role in enhancing the efficiency of Concentrated Solar Technologies (CST) by improving the measurement and prediction of flux density in solar power plants. As part of our team, you will work on the practical implementation of a pioneering technique with real-world applications. Your contributions will directly impact two European-level projects focused on developing and testing this technology. You will gain hands-on experience in high-performance computing and advanced image processing for real-time predictions, working alongside a multidisciplinary team at the intersection of AI, engineering, and energy systems.
We offer you maximum flexibility: The tasks can be completed as part of an internship or as part of a thesis (both Bachelor's and Master's theses). Just talk to us about the conditions of your studies!
If you are passionate about AI, renewable energy, and cutting-edge technology, we encourage you to join our team and contribute to shaping the future of solar power optimization! 🌞
Your tasks
- Collect reflectivity data to train and validate deep learning models.
- Implement and train models using the PyTorch framework.
- Develop data pipelines to ensure seamless data flow throughout the algorithm.
- Test and refine methods through real-world experiments.
Your profile
- Currently studying engineering, electrical engineering, mechanical engineering, computational engineering science, or a similar scientific field.
- Proficient in Python and experienced in machine learning and PyTorch.
- Familiar with the fundamentals of concentrated solar power plants and heat transfer.
- Motivated and eager to work in a team-oriented environment.
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 818) please contact:
Felix Göhring
Tel.: +49 2461 93730 209
