Fully Funded PhD Position in Data-Assisted Real-Time Simulations of Particulate Flows at JKU Linz Johannes Kepler University Linz in Austria

Johannes Kepler University Linz (JKU Linz) in Austria is offering a fully funded PhD position in the field of Data-Assisted Real-Time Simulations of Particulate Flows. This research opportunity focuses on the integration of advanced machine learning techniques with traditional computational fluid dynamics (CFD) and discrete element methods (DEM) to model and simulate complex particulate flows in industrial settings. The project aims to develop real-time digital twins of industrial furnaces and particulate systems, leveraging deep learning and surrogate modeling to reduce computational costs while maintaining high accuracy.

Key research areas include data-assisted computational modeling, fluid dynamics, machine learning, deep learning, and the application of these methods to powder metallurgy and high-tech manufacturing processes. The ultimate goal is to help industries reduce energy consumption and CO2 emissions by optimizing industrial processes through innovative simulation techniques.

The position is fully funded, providing financial support for the duration of the PhD. The announcement is made by Dr. Abdullah S., a researcher based in the USA, with a strong professional presence on LinkedIn. While specific eligibility requirements and application procedures are not detailed in the post, candidates interested in computational modeling, machine learning, and industrial applications are encouraged to apply.

For more information and to apply, candidates should refer to the LinkedIn post or the official JKU Linz website for detailed instructions and requirements.