Area of research:
Scientific / postdoctoral posts,Other
The DLR Institute of Atmospheric Physics studies the physics and chemistry of the global atmosphere from the ground to the upper edge of the middle atmosphere at an altitude of about 120 km. As an institute of the German Aerospace Center, the institute addresses questions regarding the atmosphere relevant to DLR in the HGF programs of Aeronautics, Space, Transport and Energy. To this end, the institute covers the entire spectrum of methods ranging from sensor development, observations on different spatial scales (local to global), analysis, theory to numerical modeling including future projections.
The Earth System Model Evaluation and Analysis Department develops innovative methods to improve Earth system models and their evaluation with observations with the aim to better understand and project climate change. The evaluation and ensemble analysis of Earth system models is essential to continuously improve the models and a prerequisite for reliable climate projections of the 21st century, which are used in climate policy guidelines. In order to improve the routine and comprehensive evaluation of climate models, the department is leading the development of the Earth System Model Evaluation Tool (ESMValTool). A major focus of the department is the development and application of machine learning (ML) methods to improve the understanding and modeling of the Earth system.
Quantum computers are one of the ground-breaking novel technologies of the 21st century. They will make it possible to perform calculations and simulations that conventional computers would need a prohibitive amount of time for. With the Quantum Computing Initiative, DLR has begun a concerted effort to build quantum computers for Europe and unlock their potential for pioneering applications.
Building on work that is done in the European Research Council (ERC) Synergy Grant on „Understanding and Modelling the Earth System with Machine Learning (USMILE, www.usmile-erc.eu/)“ , a new project on “Improving Climate Models with Quantum Machine Learning for Robust Technology Assessments and Mitigation (KLIM-QML)” within the Earth System Model Evaluation and Analysis Department will develop a prototype for a quantum machine learning (QML) based climate model where physical sub-grid scale parametrizations are replaced with QML approaches. The unique opportunities that quantum computing offers are explored to help make climate models and their development process better and faster. This work will be done in close collaboration with industry partners.
In this position, you will first perform literature research and develop a concept to tune a climate model using quantum computers, and then implement the developed approach on the example of the general atmospheric circulation model ICOsahedral Nonhydrostatic (ICON). You will compare the newly tuned ICON model with observational data using the ESMValTool developed at the Institute of Atmospheric Physics and apply it to a use case.
- Development of methods to tune climate models using quantum computers
- literature research and application of literature to develop a concept for tuning climate models using hybrid quantum computers
- implementation of the developed tuning approach
- evaluation of the tuned model with the ESMValTool
- application to a use case
- development of documentation and software
- publication of the results
This research center is part of the Helmholtz Association of German Research Centers. With more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation.
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