Hybrid Master Thesis (f/m/x) - QML-based parameterization of the boundary layer height (Oberpfaffenhofen) bei Deutsches Zentrum für Luft- und Raumfahrt
Deutsches Zentrum für Luft- und Raumfahrt · Oberpfaffenhofen, Deutschland · Hybrid
- Optionales Büro in Oberpfaffenhofen
The DLR Institute of Atmospheric Physics in Oberpfaffenhofen conducts research into the physics and chemistry of the global atmosphere from the ground
up to 120 km altitude.
What you can expect
The Department of Earth System Model Evaluation and Analysis develops innovative methods for evaluating and analysing Earth system models in comparison with observational data with the aim of better understanding and predicting the Earth system. In the Klim-QML project, we are developing the first prototype of a climate model improved with quantum machine learning (QML) methods.
Your tasks
- Development of a QML-based parameterisation for the boundary layer height
- carrying out simulations with the ICON-XPP earth system model to generate training data
- Compression of the training data for use in a QML model
- Documentation and software as open source
Your profile
- enrolled in a master's program in physics, quantum technology, computer science or a similar field
- very good programming skills (preferably Python), including machine learning methods
- Enthusiasm, motivation and creativity
- fluency in English (written and spoken)
- Experience in quantum machine learning or climate modelling is an advantage
Depending on qualification and assingnment of tasks, remuneration will be up to pay grade EG05 TVöD Bund.
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 2539) please contact:
Mierk Schwabe
Tel.: +49 8153 28 4239
