Steigen Sie ein in die faszinierende Welt des Deutschen Zentrums für Luft- und Raumfahrt (DLR), um mit Forschung und Innovation die Zukunft mitzugestalten! Mit dem Know-how und der Neugier unserer 11.000 Mitarbeitenden aus 100 Nationen sowie unserer einzigartigen Infrastruktur, bieten wir ein spannendes und inspirierendes Arbeitsumfeld. Gemeinsam entwickeln wir nachhaltige Technologien und tragen so zur Lösung globaler Herausforderungen bei. Möchten Sie diese große Zukunftsaufgabe mit uns zusammen angehen? Dann ist Ihr Platz bei uns!
For our Institute of Atmospheric Physics in Oberpfaffenhofen close to München we are looking for a Physicist, mathematician, meteorologist, computer scientist or similar (f/m/x), Development of methods for coupling shadow models of QML-based parameterizations with ICON
Das erwartet Sie:
The Institute of Atmospheric Physics deals with relevant questions of atmospheric research with reference to the programs of the Helmholtz Association of German research institutions: Aeronautics, Space, Transport and Energy. Quantum computers are one of the pioneering new technologies of the 21st century. They will enable calculations and simulations that would take conventional computers a prohibitively long time. With the DLR Quantum Computing Initiative, DLR has launched a concerted effort to build quantum computers for Europe and to realize their potential for ground-breaking applications. Within the Quantum Computing for Earth System Models group, we develop the first prototype of a climate model improved with quantum computers. Building on the work carried out within the Synergy Grant of the European Research Council (ERC) on "Understanding and Modelling the Earth System with Machine Learning (USMILE, https://www.usmile-erc.eu/)", the Klim-QML project develops quantum machine learning (QML)-based models to replace physical parameterizations at the subgrid level in the climate model ICON. The unique possibilities offered by quantum computing are explored to improve and accelerate climate modelling and its development process.
As part of this research field, your tasks will include the following activities:
Development of methods for coupling shadow models of QML-based parameterisations with ICON
* literature research and its application to train shadow models of QML-based parameterizations
o training shadow models that retain the properties of QML models as far as possible, but run on classical computers
o testing the developed models with available quantum computers and simulators and analyzing their scalability
o coupling the shadow models with the ICON climate model
* evaluation of the simulations using the ESMValTool
o comparison with conventional models
o comparison with observational data
o creation of documentation and software
Das erwarten wir von Ihnen:
* completed scientific university degree (diploma/master's degree) in the natural sciences, for example physics, mathematics, meteorology or in data science, computer science or a comparable field of study
* very good doctorate in physics, meteorology, mathematics, data science, computer science or a comparable field of study
* experience in working independently on complex research tasks
* proven scientific excellence through publications or similar
* experience in dealing with very large amounts of data and machine learning methods
* advanced knowledge of quantum computing or climate modelling
* very good programming skills, preferably Python
* very good English language skills
* willingness to travel
* very good communication and teamwork skills
* excellent analytical skills
* A prerequisite for employment at DLR is security clearance in accordance with the Security Clearance Act (SÜG) and the willingness to undergo a security check in accordance with §8 ff SÜG.
Unser Angebot:
Das DLR steht für Vielfalt, Wertschätzung und Gleichstellung aller Menschen. Wir fördern eigenverantwortliches Arbeiten und die individuelle Weiterentwicklung unserer Mitarbeitenden im persönlichen und beruflichen Umfeld. Dafür stehen Ihnen unsere zahlreichen Fort- und Weiterbildungsmöglichkeiten zur Verfügung. Chancengerechtigkeit ist uns ein besonderes Anliegen, wir möchten daher insbesondere den Anteil von Frauen in der Wissenschaft und Führung erhöhen. Bewerbungen schwerbehinderter Menschen bevorzugen wir bei fachlicher Eignung.
Weitere Angaben:
* Eintrittsdatum: sofort
* Dauer: 31.12.2026
* Vergütung: Je nach Qualifikation und Aufgabenübertragung bis Entgeltgruppe 13 TVöD.
* Kennziffer: 98383