项目介绍

2026年6月11日

Project
Join a research initiative in the field of Industry 4.0 and cyber-physical systems. The aim of the project is to develop a digital twin for precoat filtration processes and to use it within a model predictive control framework. Precoat filtration is an industrially established separation process in which, in particular, the optimal dosing of filter aids and the prediction of process behavior are still not yet sufficiently understood. The project will develop a mechanistic model that uses real-time data to describe future process behavior and make it usable for optimized process operation. The focus is on the modeling, numerical implementation, and control-oriented use of this digital twin. This includes the development of efficient simulation methods, the integration of measurement data for state reconstruction, and the implementation of model predictive control strategies with regard to operating costs, energy consumption, and product quality. The work will be carried out in close cooperation with an experimentally oriented partner research group and will combine methodological research with industrially relevant applications.

Your Profile
You have completed an above-average Master’s degree in process engineering, chemical engineering, mechanical engineering, technical mathematics, or a related field. We expect knowledge of mathematical modeling, numerical simulation, or control engineering, as well as programming experience, for example in Matlab or Python. Initial experience with partial differential equations, optimization methods, or model-based control concepts is an advantage. You work independently and analytically and are interested in interdisciplinary research at the interface of modeling, data integration, and process control.

Our Offer
The position is available at the earliest possible date and is suitable for pursuing a doctorate. You will work in a scientifically demanding yet application-oriented research environment with a close connection to current questions of digitalization in process engineering. You can expect a diverse research project at the interface of modeling, data integration, and control, as well as collaboration with an experimentally oriented partner research group and strong industrial relevance. Applicants with severe disabilities will be given preference in cases of otherwise essentially equal suitability, ability, and professional performance. TUM aims to increase the proportion of women and therefore expressly encourages qualified women to apply.

Application
If you are interested in this position, we look forward to receiving your application at svt-jobs@wzw.tum.de. If you have any questions, please feel free to contact:

Technische Universität München
Chair of Process Systems Engineering
Prof. Dr.-Ing. Heiko Briesen
Gregor-Mendel-Straße 4, 85354 Freising
Tel. +49 8161 71-3271
Heiko.Briesen@tum.de
www.lse.ls.tum.de/svt