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Technical University of Munich

PhD/ Post-Doc – Human-Centric Control and Personalised Machine Learning for Rehabilitation Robotics

The Chair of Information-Oriented Control invites applications for exceptional doctoral and postdoctoral researchers in rehabilitation robotics, focusing on human-centric modelling and control, personalisation via robust machine learning, and adaptive control strategies for assistive systems such as exoskeletons and neuromodulation techniques.

Our research is at the interface of control theory, neuromechanical modelling, neurorehabilitation, and machine learning. The aim is to develop principled methods for personalised assistance and recovery, enabling novel approaches to control and adapt robotic and stimulation-based systems to individual users. Applications include the coordination of wearable exoskeletons and FES, learning-based trajectory adaptation, and uncertainty-aware control in human–robot interaction.

We are looking for highly motivated individuals with a strong disciplinary background and a keen interest in interdisciplinary research.

About us:

At the Chair of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams, haptic assistance, cyber-physical systems, and infrastructure systems. While our core competence is control engineering and robotics, we have some interdisciplinary collaborations with the fields of psychology (in human-robot interaction) and communications (in networked control systems). Many of the developed methods are experimentally validated in our multi-robot lab.

To learn more about our research and ongoing projects, we invite you to read our current publications and visit the websites of our individual team members. If you have questions about our group culture or specific research topics, please feel free to contact us. However, make sure to first check the FAQs to see if your question has already been answered.

Your profile:

  • Completed university degree in engineering, computer science, mathematics, physics, or a comparable field.
  • Enthusiasm, creativity, and the ability to work independently and responsibly.
  • Convincing academic record.
  • Solid knowledge of control theory and machine learning, ideally also statistics and robotics.
  • Experience with higher-level programming languages such as C++, Python, MATLAB, or Julia.

We offer:

Application:

Please send your application including a motivation letter, your complete CV, grades, relevant certificates, and some of your publications to

Univ.-Prof. Dr.-Ing. Sandra Hirche
Lehrstuhl für Informationstechnische Regelung
Technische Universität München
80290 München

Electronic applications in a single pdf file by Email to applications.itr(at)xcit.tum.de

TUM is especially encouraging minorities and women to apply, because of its strong commitment to diversity in engineering education, research, and practice.

 

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