Research Associate / Doctoral Candidate (m/f/d) “Model Predictive Control and Digital Twin for Filtration Processes”Full PhD

Working Language
German, English
Location
Freising
Application Deadline
31 Jul 2026
Starting Date
as soon as possible

Overview

Open Positions

1

Time Span

as soon as possible for 4 years

Application Deadline

31 Jul 2026

Financing

yes

Type of Position

Full PhD

Working Language

  • German
  • English

Required Degree

Master

Areas of study

Chemical Engineering, Process Technology, Mechanical Engineering, Mathematics

Description

Description

The Chair of Process Systems Engineering at the Technical University of Munich (Freising campus, School of Life Sciences) is seeking a research associate / doctoral candidate (m/f/d) for the “Development of a digital twin and model predictive control for filtration processes”.

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 at 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 at tum.de

Home - Chair of Process Systems Engineering

Data protection notice: As part of your application for a position at the Technical University of Munich (TUM), you submit personal data. Please note our data protection information pursuant to Art. 13 of the General Data Protection Regulation (GDPR) regarding the collection and processing of personal data in the context of your application, available at http://go.tum.de/554159. By submitting your application, you confirm that you have taken note of TUM’s data protection information.

Required Documents

Required Documents

  • CV
  • Certificates
  • Motivation letter
  • Transcripts
  • References