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Friedrich-Alexander Universität Erlangen-Nürnberg

Just Landed

PhD Position in Electrotomographic Imaging of Two-Phase Flows Friedrich-Alexander University Erlangen-Nuremberg in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

Full-time temporary employment under the TV-L E 13 pay scale; weekly working hours are by appointment. The position is a temporary research project.

Deadline

Nov 30, 2026

Country flag

Country

Germany

University

Friedrich-Alexander Universität Erlangen-Nürnberg

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Chemical Engineering
Artificial Intelligence
Two-phase Flow
Pipe Flow
Physics
ML

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About this position

Friedrich-Alexander University Erlangen-Nuremberg is offering a PhD position at the Institute of Multiscale Simulation of Particulate Systems, led by Prof. Thorsten Pöschel. The research is based in the Department of Chemical and Bioengineering in Erlangen, Germany.

The project develops reliable methods for characterizing liquid–gas bubble mixtures in pipe flows using electrical impedance tomography (EIT). The PhD researcher will investigate electrotomographic imaging of two-phase flows, with the work combining experimental or computational flow analysis, electrical measurement methods, and interpretation of complex multiphase-flow data.

The research environment brings together particulate-system simulation, chemical and bioengineering, programming, data analysis, artificial intelligence, and machine learning. The position is suited to researchers interested in applying computational and data-driven approaches to the imaging and characterization of industrially relevant bubble flows.

Funding details

Full-time temporary employment under the TV-L E 13 pay scale; weekly working hours are by appointment. The position is a temporary research project.

What's required

A Master's degree in physics, mechanical engineering, materials science, computational engineering, computer science with a strong interest in physics, or a related subject is required. Applicants should have very good programming skills, preferably in C++ and Python, as well as skills and experience in data analysis, artificial intelligence, and machine learning. Application documents should include a cover letter, CV, certificates, references, and any other relevant materials.

How to apply

Submit a cover letter, CV, certificates, references, and other relevant materials by email to [email protected]. Questions about the position or application process can be directed to Professor Thorsten Pöschel.

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