Master Thesis “Active flow control using machine learning approaches” in Graz bei Virtual Vehicle Research GmbH
Master- / Diplomarbeit bei Virtual Vehicle Research GmbH

Master Thesis “Active flow control using machine learning approaches”

Virtual Vehicle Research GmbH, Graz

VIRTUAL VEHICLE is a leading international R&D center for the automotive and rail industries. The center focuses on advanced virtualization of vehicle development. This linking of numerical simulations and hardware testing leads to a powerful HW-SW system design.


  • Literature study for active flow control using machine learning approaches
  • Definition of the reduced thermal comfort use case
  • Specification of the machine learning approach
  • CFD simulation setup in OpenFOAM for thermal comfort use case
  • Machine learning framework in Keras for thermal comfort use case and interface communication
  • Derived active flow control strategies for predefined scenarios using the machine learning framework


  • Studies Mathematics, Technical Mathematics, Physics, Mechanical Engineering
  • Basic knowledge in Linear Algebra, Numerical Mathematics, Probability Theory
  • Fluid Dynamics and Heat Transfer
  • Basic programming skills: Python and C/C++ on Linux or Windows
  • Knowledge in machine learning frameworks (Tensorflow, Keras) and/or OpenFOAM is beneficial


  • Collaboration and contribution in an engaged, dynamic team
  • Interesting work in an international research center
  • Paid Thesis
  • Mentoring programme
  • Professional and personal development opporturnities
  • Diverse sports and health activities
  • Corporate events

For technical questions, please contact Alexander Kospach,, +43-(0)316-873-9055.

Supervision by

Univ.-Ass. Mag.rer.nat. Dr.rer.nat. Manfred Liebmann University of Graz / Institute for Mathematics and Scientific Computing


Master- / Diplomarbeit
Ab sofort
Inffeldgasse 21A, 8010 Graz
Paid Thesis
Virtual Vehicle Research GmbH
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