Research Associate (f/m/d) Research focus: Disruptive aerodynamic design approaches

Modern // regional // industry-oriented: The Brandenburg University of Applied Sciences (Technische Hochschule Brandenburg, THB) is a young and dynamic university with approximately 3,200 students enrolled in 26 study programs across the Departments of Computer Science & Media, Engineering, and Business Administration, located in the city of Brandenburg an der Havel — directly at the doorstep of Potsdam and Berlin. As a family-friendly university on a green campus, we offer attractive working conditions.

Within the Department of Engineering, as part of the research project DaHKIZ (Data-based Holistic AI-supported Civil Engine Development), the following position with the opportunity to pursue a doctoral degree is to be filled at the earliest possible date, initially limited until 30 April 2029: in cooperation with Rolls-Royce Dtl.

Research Associate (f/m/d) Research focus: Disruptive aerodynamic design approaches
You work in the field of disruptive design approaches on the investigation of new methods for the evalua-tion of engine components. As classical designs for intake, nacelle and nozzle increasingly reach physical limits, disruptive concepts (e.g. active flow control, morphing geometries) shall be investigated. Your fo-cus lies on the development and application of AI/ML methods to assess the potential of these approaches quickly, in a data-based and reliable manner.

Your main responsibility

Method development: you compare and decide on methods of Machine Learning (ML) and Artificial Intelligence (AI), such as Variational Autoencoders or GANs, to efficiently analyze high-dimensional design spaces even with sparse data.
Simulation setup: you create parametric geometries and build simulation chains as "virtual test rigs" for components such as intake, nacelle, bypass duct as well as nozzle and mixer.
Implementation & training: you prototype selected AI/ML models (e.g. PINNs, graph-based models) within the simulation environment and perform training using large data sets.
Scientific verification: you systematically verify the developed models with respect to robustness, physical limits, sensitivities and uncertainty quantification.
Publication: you prepare scientific publications and present the results at international conferences.

Your profile

Successfully completed academic university degree (Master's or University Diploma) in a relevant discipline (Aerospace Engineering, Mechanical Engineering, Physics, Computer Science or similar).
Sound knowledge of the fundamentals of Machine Learning, as well as of numerical fluid mechanics (CFD) or aerodynamics.
Confident use of Python or equivalent
Very good English language skills, both written and spoken (level C1), for the preparation of international publications.

The university expressly encourages qualified women to apply. In the event of equal aptitude, qualifications and professional performance, applications from persons with recognized severe disabilities will be given preferential consideration. Please indicate any severe disability already in your application. The HR Department (+49 3381 355-113, leitung-pvo@th-brandenburg.de) and the Equal Opportunities Officer (+49 3381 355-443, gba@th-brandenburg.de) are available for consultations regarding individual questions. For further information, please also see https://www.th-brandenburg.de.

For further information on the advertised position, Mr Prof. Flassig is available by email at flassig@th-brandenburg.de. For questions regarding the application process or for any other support, please feel free to contact Ms Peters by email at doreen.peters@th-brandenburg.de.

Please apply by 22.10.2026 via our online application portal, quoting the reference number listed above.

We look forward to receiving your application!