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Helmholtz-Zentrum Hereon

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PhD Position in Physics-Guided Digital Twin Development for Materials and Manufacturing Helmholtz-Zentrum Hereon in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

This is a 4-year PhD position at Helmholtz-Zentrum Hereon. Remuneration is offered up to pay group 13 according to the TV EntgO Bund collective agreement, together with public-service social benefits. The package also mentions six weeks of holiday per year and additional workplace and family-related benefits.

Deadline

Nov 12, 2026

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Country

Germany

University

Helmholtz-Zentrum Hereon

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Keywords

Computer Science
Mechanical Engineering
Materials Science
Manufacturing Engineering
Computational Mechanics
Reinforcement Learning
Digital Twin Technology
Explainable Ai
Physics

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About this position

Helmholtz-Zentrum Hereon is offering a four-year PhD position in physics-guided digital twin development at the Institute of Material and Process Design in Geesthacht, Germany. The project combines machine learning with computer simulations to address complex problems in materials science, computational engineering and advanced manufacturing.

The doctoral researcher will develop supervised, unsupervised and reinforcement-learning models for clustering, classification and regression. These models will be combined with, enhanced or used in place of established computational approaches such as the finite element method and constitutive materials models. The scientific aim is to represent and exploit relationships across the composition-process-structure-property-performance chain.

Applications will focus on manufacturing techniques for lightweight structures. The resulting physics-guided digital twins are intended to support the stability and control of novel manufacturing processes and enable the design of materials with targeted properties. The work will also combine simulation data with experimental measurements while accounting for uncertainty.

Additional research activities include explainable AI for scientific discovery and evaluation of system architectures such as Retrieval-Augmented Generation for data retrieval and knowledge inference. The researcher will implement machine-learning pipelines in Python, using tools such as PyTorch, and validate results with colleagues from multiple application areas.

The PhD will be supervised by Prof. Noomane Ben Khalifa, affiliated with Hereon and Leuphana University Lüneburg, and supported by Dr.-Ing. Frederic Bock. The Institute of Material and Process Design works on sustainable materials and manufacturing processes, particularly for transportation and medical technology, within Hereon's interdisciplinary international research environment.

Funding details

This is a 4-year PhD position at Helmholtz-Zentrum Hereon. Remuneration is offered up to pay group 13 according to the TV EntgO Bund collective agreement, together with public-service social benefits. The package also mentions six weeks of holiday per year and additional workplace and family-related benefits.

What's required

Applicants must hold a master's degree in mechanical engineering, materials science, computational engineering, computer science, applied mathematics, physics or a similar field. Very good Python programming skills, prior experience with neural networks and common Python machine-learning libraries such as PyTorch, background knowledge in computational mechanics and materials science, and highly proficient spoken and written English are required.

How to apply

Apply through the official Hereon job advert by selecting “Apply now” and submitting the required application materials through the online application portal.

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