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Master Thesis (f/m/x) - Deep Learning-Based Cloud-Base Height Retrieval
Job Description
Req ID:  3668
Place of work:  Almeria
Starting date:  01.02.2026
Career level:  Student research project and final thesis
Type of employment:  Part time, Full-time
Duration of contract:  6 Monate

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The Institute of Solar Research develops innovative technologies for the utilisation 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.

 

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 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 offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 3668) please contact:

 

Stefan Wilbert 
Tel.: +49 2203 601 4619