Aerospace Engineer, Mathematician, Computer Scientist or equivalent (f/m/x)

The Institute of Aerodynamics and Flow Technology is a leading research institute in the field of aerodynamics/aeroacoustics of airplanes and aerothermodynamics of space vehicles. The main activity of the C²A²S²E department (Center for Computer Applications in AeroSpace Science and Engineering) is the development of numerical methods and processes for the multi-disciplinary simulation and optimization of aircraft - from flight physics design to virtual certification.

We develop physical models for complex flows and cutting-edge solution algorithms, efficient optimization strategies covering all relevant disciplines, as well as surrogate models based on high-fidelity methods. The customization of numerical methods for optimal efficiency on high-performance computer clusters is of particular importance to the department. The flow-solvers being developed at C²A²S²E are routinely used for a wide range of applications in academia, research and industry throughout Germany and Europe.

Your main responsibility is the development, implementation and practical application of self-learning aerodynamic models. The goal is to develop models that allow to accurately represent the operational behavior of aircraft and wind turbines over the entire life cycle. To do this, you will investigate advanced machine learning methods which yield models that can learn and improve autonomously based on continuous data-streams. Together with colleagues, you will have the chance to apply and evaluate the methods you have developed in several wind tunnel experiments. The wind tunnel tests cover wind energy as well as civil aviation. This offers you the unique opportunity to bring your research in the field of machine learning to life under realistic conditions in DLR's large-scale research facilities.

Your qualifications:

  • university degree (Master / diploma) in the natural sciences (e.g. mathematics, computer science) or engineering (e.g. aerospace engineering) or other courses of study relevant to the job
  • good knowledge in the field of machine learning with a focus on self-learning models
  • knowledge in the field of aerodynamics
  • practical experience in developing software in python
  • ability to work independently as well as within a small-sized, agile team
  • proficient communication skills in English, both written and spoken
  • previous research experience (PhD) advantageous
  • knowledge of aircraft aerodynamics desirable
  • ideally Knowledge and experience in performing wind tunnel experiments
  • ideally, proven skills in publishing and presenting scientific results and presenting scientific topics to external partners
  • basic knowledge in the field of numerical methods and scientific computing is a plus

Your benefits:

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

Visit employer page

Deadline: 2023-08-17
Location: Germany, Braunschweig
Categories: Aerospace Engineering, Computer Engineering, Computer Sciences, Engineering, Machine Learning, Mathematician, Mathematics,


Universität der Bundeswehr München

FVB - Leibniz Forschungsverbund Berlin

DSMZ - Leibniz-Institut / Deutsche Sammlung von Mikroorganismen und Zellkulturen

TU Darmstadt

ISST - Fraunhofer-Institut / für Software- und Systemtechnik

University of Basel

Aarhus University

Bayer AG

More jobs from this employer