PhD position on physics-based machine learning modeling for materials and process design

Helmholtz-Zentrum Geesthacht, Germany

Updated: about 18 hours ago
Location: Geesthacht, SCHLESWIG HOLSTEIN
Deadline: 26 Apr 2026

The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with, enhance or replace established methods from computational engineering and computer simulation (such as the finite element method and constitutive materials models) to represent and exploit relationships along the composition-process-structure-property-performance chain; therefore, enable stability and control of novel manufacturing processes as well as achieving desired properties within materials science and engineering. Use cases will be defined within different manufacturing techniques of lightweight structures to enable novel development of materials and process design.

The PhD position will be supervised by Prof. Noomane Ben Khalifa (Hereon/​​Leuphana University Lüneburg) and supported by Dr.‑Ing. Frederic Bock (Hereon).

The objective is to combine computer simulations and machine learning models to extend their compatibility with problems from mechanical engineering and materials research that could not be addressed so far due to their high complexity, which prevents approaches that solely rely on classical mechanistic modeling or classical machine learning.

Equal opportunity is an important part of our personnel policy. We would therefore strongly encourage qualified women to apply for the position.


Severely disabled persons and those equaling severely disabled persons who are equally suitable for the position will be considered preferentially within the framework of legal requirements.

Then we are looking forward to receiving your comprehensive application documents (cover letter, CV, transcripts, certificates etc.) indicating the reference number 2026/WD 1 (980) until April 26th, 2026.


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