Master Thesis „Deep Learning-Based Cloud-Base Height Retrieval“

The Institute of Solar Research develops innovative technologies for the utilization of solar energy. The focus is on electricity generation and the provision of heat and fuels. The primary goal is to use solar energy to contribute to the heat transition and a reduction in fossil fuels. In our subgroup Energy Meteorology we are currently looking for a master student to work on the following project.

What to expect
You will work on AI-based, spatially resolved short-term solar irradiance forecasts that aim to enable the integration of PV power plants into the balancing energy market. This involves using data from high-resolution all-sky imagers operated by DLR near Oldenburg and in Almería, which capture cloud dynamics that drive PV power variability. Your main focus will be on developing machine-learning methods to improve cloud-base-height (CBH) estimation, as existing models still show significant errors.

You will be part of a diverse and motivated team working on energy-transition topics and contributing to climate protection. Close collaboration with supervisors and colleagues will support you in exchanging ideas and solving challenges. You will gain hands-on experience in machine learning, software development, automated testing, version control and modern image-processing technologies. A particular highlight of the project is the opportunity to work in Almería, one of the sunniest locations in Europe.

Your tasks

• Conduct a literature review on fundamentals and use cases (in Earth Sciences) of applicable machine learning methods
• Develop a deep-learning-based model for CBH estimation including innovative pre-extraction of the sky images’ features
• Train your model end-to-end using carefully designed and high-quality ground truth labels
• Benchmark your models against existing CBH detection techniques and analyze their performance
• Summarize your methodology, experiments and results in a well-structured master thesis

Your profile

• You have a strong academic record in a master’s program in computer science, physics, mathematics engineering or a related field.
• Experience in Python and basic knowledge about machine learning
• The ability to work independently and collaborate in an international team
• Prior experience in data analysis, computer vision and git versioning systems
• Confident in speaking and writing English

We look forward to getting to know you! Ideal but flexible starting date 01. March 2026 

If you have any questions about this position, contact Milon Miah (he/him) (milon.miah@dlr.de)

Please apply via the DLR Job Portal (Vacancy-ID 3668)