Reconstruction Algorithms for EIT

Electrotomographic Imaging of Two-Phase Flows

Location: Friedrich-Alexander-Universität Erlangen, Germany; Institute for Multiscale Simulation
Duration: 36 months
Start: as soon as possible

Project overview: The aim of the project is to reliably characterise the liquid-gas bubble mixture in pipe flows using electrical impedance tomography (EIT). An important application is the real-time analysis of coolant flow in the pipes of (nuclear) power plants, where the cooling performance depends crucially on the state of the liquid-gas bubble mixture.
Like all tomographic methods, EIT requires a numerical reconstruction method to generate a three-dimensional image of the bubble flow from the measured complex resistance values. In the case of EIT, this is a poorly posed mathematical problem for which no clear mathematical solution exists.
The elaboration of reliable and efficient approximate numerical methods for interpreting EIT measurements is the subject of the PhD project. Methods of artificial intelligence and machine learning will be applied.

Profile of the ideal applicant:

We look for a PhD student with the following qualifications:

  • Master’s degree in physics, mathematics, computational engineering, computer science, or related subjects
  • Very good programming skills, preferably in C++ and Python
  • Skills and experience in data analysis, artificial intelligence, and machine learning
  • Strong academic writing skills and clear communication skills in English
  • Ideally (but not mandatory) knowledge of the German language

Scientific environment: The position is fully funded through a grant from the Federal Ministry of Education and Research. The workplace is the Institute for Multiscale Simulation (MSS). The PhD student will develop the reconstruction algorithms for interpreting EIT measurements in close cooperation with the other PhD students, postdoctoral fellows, and professors at the MSS. In particular, we expect the PhD student to work closely with the experimenters at MSS, who are also involved in EIT measurements.

This position offers an exceptional multidisciplinary environment with close collaboration between simulation and experiment, access to high-performance computing resources, and interactions with researchers at MSS and across the Friedrich Alexander University.

Salary and conditions: The position is paid according to the German income scheme for public service, level TVL E13 (percentage dependent on qualification). The position is for 2 years with the option of an extension.

Application: Your application shall contain the following documents as a single pdf file.

  • a short motivation letter
  • your complete CV
  • certificates of academic qualifications
  • links where your bachelor’s and/or master’s theses can be obtained
  • any other links or documents that will help us assess your qualifications in the field of modeling and simulation, such as presentations, participation in open-source projects
  • names and addresses of 2-3 colleagues whom we can contact to inquire about your qualifications

Send your application to mss-recruitment@fau.de with the reference number MSS-2025-FRASCAL. If you have any questions about the position or the application process, please contact Prof. Thorsten Pöschel, thorsten.poeschel@fau.de .

The selection process will begin immediately and continue until a suitable candidate is found.