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

Geesthacht
Helmholtz-Zentrum Hereon
Designer
Inserat online seit: Veröffentlicht vor 11 Std.
Beschreibung

Helmholtz-Zentrum Hereon

The Helmholtz-Zentrum Hereon conducts cutting-edge international research for a changing world: Around 1,000 employees contribute to the tackling of climate change, the sustainable use of the world's coastal systems and the resource-compatible enhancement of the quality of life. From fundamental research to practical applications, the interdisciplinary research spectrum covers a unique range.


Institute of Material and Process Design

The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative materials and manufacturing processes, especially for the transportation sector and medical technology. To this end, materials are tailored and manufacturing processes are designed to conserve resources – from the modeling of material behavior to the development of the material to the finished component.


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

Reference code: 980 - 2026/WD 1
Commencement date: as soon as possible
Work location: Geesthacht
Application deadline: April 26th, 2026

The Institute of Material and Process Design at the Helmholtz-Zentrum Hereon is offering a 4‑year PhD position in the area of machine learning and computer simulations. 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.


APCT1_DE

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