Computer Scientist, Data Scientist, or similar, Research Software Engineer (f/m/x)

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,“, 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 apply and further develop hybrid quantum and conventional algorithms for accelerating climate simulations and for data compression on quantum computers and simulators. In addition, you will run high-resolution climate simulations and support the group members on evaluating the simulations in comparison with observations using the ESMValTool developed at the institute.

Technical development of hybrid algorithms on conventional/quantum computers to accelerate climate simulations and for data compression

  • Further development and adaptation of quantum algorithms to accelerate climate models and their development process
  • Application of algorithms for data compression for use on quantum computers
  • Technical support of the department members in the implementation and development of algorithms for quantum computers on different high performance and quantum computers
  • Publication of results in journals on machine learning and quantum computing
  • Documentation of software and results

Running high-resolution climate simulations and technical support in their evaluation

  • Performing high-resolution ICON simulations
  • Technical support of other group members in planning and post-processing of ICON simulations
  • Technical support in the development of diagnostics for the evaluation of the simulations with the ESMValTool
  • Technical assistance in the processing of high-resolution climate simulations with the ESMValTool
  • Documentation of the results
  • Degree (Bachelor or Master) in computer science, scientific computing, data science or comparable field 
  • Good knowledge of machine learning
  • Very good knowledge of programming with Python
  • Knowledge of software engineering incl. tools
  • Interest in quantum computing, ideally previous knowledge of it
  • Knowledge of Unix / Linux
  • Very good written and spoken English
  • Willingness to travel
  • Experience in processing large amounts of data
  • Experience in the implementation of large software development projects

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x).Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

DLR - Helmholtz / Deutsches Zentrum für Luft- und Raumfahrt

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Location: Germany, Oberpfaffenhofen
Categories: Chemistry, Computer Engineering, Computer Sciences, Data Science, Machine Learning, Physics, Programming, Software Engineering,


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