The DLR Institute of Atmospheric Physics investigates the physics and chemistry of the global atmosphere from the ground to the top of the middle atmosphere at an altitude of about 120 km. The Department of Earth System Model Evaluation and Analysis develops innovative methods for the evaluation and analysis of Earth system models in comparison with observational data with the aim of better understand and predict the Earth system. A main focus of the department is the development and application of machine learning (ML) methods to improve understanding and modelling of the Earth system.

Quantum computers are one of the pioneering new technologies of the 21st century. They will enable calculations and simulations that would take prohibitively long to perform using conventional computers. With the DLR Quantum Computing Initiative, DLR has launched a concerted effort to build quantum computers for Europe and to exploit their potential for breakthrough applications. Within the project KLIM-QML, we will build the first prototype of a quantum computer-enhanced climate model. Building on the work carried out in the framework of the Synergy Grant of the European Research Council (ERC) on "Understanding and Modelling the Earth System with Machine Learning Learning" (USMILE), the KLIM-QML group is developing a prototype of a climate model based on machine learning with quantum computers (QML), in which physical parameterisations at sub-grid level are replaced by QML approaches. The unique possibilities offered by quantum computing are being explored to improve and accelerate climate models and their development process. This work is carried out in close collaboration with industry partners.

In this position you will  develop a concept of how climate models can be accelerated by means of quantum computers, and then implement this concept using the example of the general atmospheric circulation model ICOsahedral Nonhydrostatic (ICON) as an example. Please note that the working place will be at the DLR Quantum Computing Initiative in Hamburg Lokstedt.

Within the scope of this research field, your tasks will include the following activities:

• development of methods to accelerate climate model simulations with quantum computers
  • literature research and application for the conceptualisation and implementation of the acceleration of climate model simulations using quantum computing
    • performing model simulations with the ICON model
    • development of a method to accelerate the execution of model simulations with future quantum computers
    • identify a suitable toy model to use on currently available quantum computers and simulators
    • test the developed methods with available quantum computers and simulators and analyse their scalability 
• evaluation of the simulations using ESMValTool
  • comparison with conventional models
  • comparison with observational data
• preparation of documentation and software
• close cooperation with USMILE and industry partners