Austria – Fully Funded PhD in Data-Assisted Simulations at Johannes Kepler University

Overview

University: Johannes Kepler University
Country: Austria
Deadline: 2025-10-19
Fields: Physics, Applied Mathematics, Mechanical Engineering, Computational Science, Machine Learning

About the University

Johannes Kepler University (JKU) Linz is one of Austria’s leading institutions for research and higher education, renowned for its strengths in science, engineering, and technology. Located in Linz, JKU offers a modern campus environment, interdisciplinary collaboration, and innovation. Linz is a hub for technology and industry with a welcoming international community.

Research Topic and Significance

The primary focus is on data-assisted computational modeling of particulate multiscale and multiphysics flows, within the Christian Doppler Laboratory for Data-Assisted Simulations of Complex Flows. Projects aim to develop data-assisted surrogates such as recurrence computational dynamics (CD) and universal physics transformers to enable real-time simulation capabilities. A key application is the creation of digital process twins for complex particulate flows, including moving and fluidized bed reactors and rotary kilns.

The research advances data-driven modeling techniques to reduce energy consumption and CO2 emissions in industrial processes, aligning with sustainability and operational efficiency goals in manufacturing, energy, and materials processing. This approach combines physics-based modeling with machine learning for more accurate, efficient, and scalable simulations.

Project Details

These four fully funded PhD positions are part of the Christian Doppler Laboratory for Data-Assisted Simulations of Complex Flows at Johannes Kepler University. The research group is recognized for leadership in computational modeling and offers a dynamic, supportive environment. PhD candidates will have access to high-performance computing resources and opportunities for international collaborations, conference participation, and professional development. The positions offer a competitive gross salary of EUR 3,715 per month, paid 14 times per year.

Candidate Profile

The ideal candidates are highly motivated and curious with a strong academic background and passion for computational science. Suitable applicants will have:

• A Master’s degree in Physics, Applied Mathematics, Mechanical Engineering, Computational Science, or a related discipline
• Solid background in classical simulation techniques (e.g., CFD, CFD-DEM)
• Strong programming skills in at least one scientific computing language
• Interest in, or willingness to learn, deep learning or other data-driven modeling methods
• Previous experience with machine learning frameworks is beneficial, especially for positions with a strong ML focus
• Applicants with a ML background who wish to deepen their understanding of physics-based simulations are encouraged to apply

The program welcomes applicants from diverse academic and cultural backgrounds who are eager to engage in interdisciplinary research and contribute to innovative industrial solutions.

Application Process

Application deadline: 19 October 2025. To apply, candidates should submit the following documents:

• A short but honest cover letter detailing research interests and motivation to apply

Application materials should be submitted according to the instructions in the official advertisement. Please refer to the official advertisement for application details.

Conclusion

This is a unique opportunity to pursue a fully funded PhD in a leading European research environment, working on projects with significant scientific and societal impact. If you are ready to advance your expertise in data-assisted simulations and contribute to sustainable industrial innovation, consider applying.