University of Luxembourg

Post-doctoral researcher in the field of data-enhanced models for simulating industrial extrusion processes (m/f)

University of Luxembourg

Luxembourg, Luxembourg

The University of Luxembourg invites applications for the following vacancy in its Faculty of Science, Technology and Medicine:

This research project aims to improve the accuracy of swell prediction in industrial extrusion processes using a combined physics and data-driven modelling approach. This is an important industrial process at the heart of many modern manufactured products.

The post-doctoral researcher will be a member of the Computational Engineering Group within the Faculty of Science, Technology and Medicine at the University of Luxembourg. He/she will work under the supervision of a multi-disciplinary team including Dr. Jack S. Hale (, Prof. Stephane P.A. Bordas (Department of Engineering), Dr. Jörg Baller (Department of Physics), Dr. Nicolas Verdun, and Dr. Jean Dheur (Goodyear Tyre and Rubber Company).

This postdoctoral position is funded by a Fonds National de Recherché Luxembourg BRIDGES grant ‘EMDD’ in partnership with Goodyear Innovation Centre Luxembourg.


• Develop a physics-based viscoelastic flow model describing the swell of a compound exiting an extrusion die.
• Augment and enhance the physical model using a statistical data-driven approach using data acquired by the second postdoctoral researcher in the Department of Physics.
• Prepare and publish articles in international peer-reviewed journals.
• Develop strategies for effective technology and knowledge transfer back to Goodyear Tyre and Rubber Company.

For further information please contact:
Dr. Jack S. Hale (


• PhD degree in Mathematics, Physics, Computer Science, Machine Learning, Statistics, Computational Sciences, Engineering, or a related field.
• Ideal candidate has knowledge of one or more of the following topics: partial differential equations, finite element methods, finite volume methods, simulation of viscoelastic flows, Gaussian processes, Bayesian statistics, image processing. We emphasise that we do not expect the successful candidate to have knowledge in all of these areas, but to be willing and able to extend themselves in new and challenging directions.
• Strong programming skills, preferably C++ and/or Python. Knowledge of FEniCS Project (, PETSc ( and/or OpenFOAM is desirable, but not mandatory.
• Excellent command of English.


• Personal work space at the University.
• Dynamic and multicultural environment.
• Very competitive salary and excellent working conditions.
• No teaching foreseen unless the candidate desires it for career development purposes.

Candidates must submit the following documents:

• Curriculum vitae.
• List of published and/or submitted publications.
• A PDF or link to the published PhD thesis, if it is complete.

Deadline for applications: 29/02/2020.

The University of Luxembourg is an equal opportunity employer.


Please apply via recruiter’s website.