Research Associate (f/m/d) – Disruptive Aerodynamic Design Approaches in TU Brandenburg in Germany

Summary

The Brandenburg University of Applied Sciences seeks a Research Associate (f/m/d) to work on the DaHKIZ project, a data‑driven, AI‑supported initiative for next‑generation civil aircraft engine design in partnership with Rolls‑Royce Deutschland. The role involves developing machine‑learning methods, creating parametric CFD models, training AI models, validating results, and publishing scientific findings. It is a full‑time, fixed‑term position of approximately 2.5 years, offering a pathway to a PhD degree. Candidates must hold a master’s degree or equivalent, possess strong ML and CFD knowledge, and demonstrate English proficiency at C1 level. The position is based in Brandenburg an der Havel, Germany, and includes typical German university benefits and a collaborative, interdisciplinary research environment.

Key Facts

Department	Department of Engineering
Position Type	Research Associate/Doctoral Candidate
Discipline	Aerospace Engineering
Research Area	Disruptive Aerodynamic Design Approaches
Contract Duration	Initially through April 30, 2029 (~2.5 years)
Language	English (C1)
Deadline	2026-10-22
Required Documents	Curriculum Vitae (CV), Cover Letter / Statement of Interest, Academic Transcripts/Degree Certificates, Evidence of English Language Proficiency (C1), Contact Information for References/Supervisors, Indication of any disabilities (optional), Portfolio/Examples of prior work (if applicable)
Employer Contact	[email protected]

About the Project

The DaHKIZ project (Data‑based Holistic AI‑supported Civil Engine Development) investigates disruptive aerodynamic design concepts for engine components such as intakes, nacelles, bypass ducts, nozzles, and mixers. In collaboration with Rolls‑Royce Deutschland, the project applies AI/ML techniques—including variational autoencoders, GANs, and physics‑informed neural networks—to generate and optimise high‑dimensional design data, develop virtual test rigs, and validate novel concepts against physical limits.

Key Responsibilities

• Compare and evaluate ML methods for engine design analysis
• Develop and automate CFD simulation chains and parametric geometry creation
• Prototype, train, and optimise AI/ML models for aerodynamic data
• Verify and validate models through uncertainty quantification and experimental comparison
• Prepare scientific manuscripts and present results at international conferences

Required Skills

• Fundamental knowledge of machine learning algorithms and neural network architectures
• Strong understanding of numerical fluid mechanics (CFD) and aerodynamic theory
• Proficiency in Python for data manipulation and ML libraries (TensorFlow, PyTorch, Scikit‑learn)
• Ability to use or quickly learn equivalent programming languages (C++, MATLAB, Julia)
• English language proficiency at C1 level (written and spoken)

Who Should Apply

Applicants with a master’s degree or German Diplom‑Ingenieur in aerospace, mechanical, physics, computer science or related engineering fields, who have solid knowledge of machine learning and numerical fluid mechanics, are proficient in Python (or comparable languages), and can work in English at C1 level. The role is suited to researchers aiming to pursue a PhD while contributing to AI‑enhanced aerodynamic design in an industry‑university partnership.

Benefits

• Family‑friendly workplace
• Green campus environment
• Access to university facilities and professional development support
• Rolls‑Royce partnership resources and international research collaboration
• Potential PhD supervision and degree award
• Standard German employment benefits (social security, statutory vacation, occupational health & safety, works council representation)
• Diversity and inclusion statements encouraging women and applicants with disabilities

About the Employer

Brandenburg University of Applied Sciences (Technische Hochschule Brandenburg) is a modern applied‑sciences university founded recently, located in Brandenburg an der Havel, Eastern Germany. It hosts around 3,200 students across three departments, emphasizing industry‑oriented, regional focus, family‑friendly policies, and a green campus setting.

Frequently Asked Questions

What is the application deadline?

The deadline is 22 October 2026.

What language proficiency is required?

English at C1 level is required.

Is the position full‑time?

Yes, it is a full‑time research position.