For the Institute of Fluid Dynamics and Ship Theory of the Hamburg University of Technology starting on 01.02.2023, we are lookingfor a:


for a maximum of  15 months. The remuneration is in accordance with TV-L 13 . 13 TV-L

No.: 32222WM8

Aircraft ditching is one safety aspect addressed during homologation of aircrafts. However, configurations and propulsion strategies currently considered for climate-neutral aircrafts require a transformation process of established safety concepts. The aim of the research is the development of a simulation method for analyzing the ditching behavior of environmentally friendly, climate-neutral commercial aircrafts and its harmonization with the design process. In this regard, intended methodological developments should combine physics and machine-learning based methods to predict the ditching loads and the related deformations of climate neutral aircrafts. Your efforts will contribute to expand current deterministic 2D+t approaches with elements from machine learning, i.e.

  • a hybrid physics-/data-driven mathematical and numerical modelling of ditching loads for unconventional fuselage shapes
  • modeling the fuselage deformation and integrate this into a two-way coupling method
  • performing high-fidelity simulations to support learning processes.

You are expected to closely collaborate with colleagues from mathematics and engineering inside academia and industry and be their interface to ditching analysis. Achievements should feed into an industrialized tool.


  • Excellent Master Degree in Industrial/Applied Mathematics or Theoretical Mechanical Engineering
  • Focus on computational fluid dynamics – knowledge of ditching process is advantageous.
  • Background and knowledge of online/offline machine learning strategies in CSE; sound background in physics and mathematics of fluids; proven background in different programming paradigms.
  • Excellent communication and team working skills.
  • Experience in the use of GPU-systems, coding competencies for TensorFlow/Keras with Python, C++, FORTRAN


    • Outside of duties, further scientific training is possible, the results can be used for a dissertation
    • Participation in structured education and training programs
    • Inter-disciplinary/methodological collaborative research at the forefront of science

    For further information please contact  Prof. Dr.-Ing. Thomas Rung

    We particularly encourage women to apply. Due to their underrepresentation, they will be given priority incases of equal suitability, qualifications and professional performance.

    Please send your complete application documents (cover letter, curriculum vitae in table form, proof ofcompleted training and/or university degree, job references or certificates of employment) via the onlineapplication system.

    We look forward to receiving your online application by December 07th 2022
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