ESR10 – ETH Zurich
ETH Zurich, Switzerland
The Intelligent Control Systems Group at ETH develops theory, algorithms and tools to make systems automatically perform challenging tasks.
The goal is to enable even safety-critical systems to leverage the potential of data and adaptation to satisfy high performance requirements in the presence of increasing complexity, uncertainty and interactions arising in modern applications. The recent success of machine learning, together with the availability of computation and sensing, motivate the use of learning techniques to address these challenges. Their wide-spread adoption in control is, however, severely limited by safety concerns when integrating learning in closed-loop decision-making. Our research addresses this problem by integrating control theory, learning and optimization. We apply the developed concepts to a range of different problems, including robotics, autonomous vehicle control, space applications, rehabilitation engineering, manufacturing, up to biomedical devices, where we mostly work in collaboration with partners from industry and academia.
The PhD will be integrated in a group with a strong focus and expertise in the domain of learning-based control. The position shall prepare the fellow for a career in advanced control engineering in industry or in academia.
• Analysis of suitable learning-based models for optimization-based control schemes (such as model predictive control) and the resulting computational properties, as well as development of tailored optimization routines.
• Efficient computational methods for dual control problems, i.e. combining exploration and exploitation.
• Efficient data selection and reduction and fast adaptation for learning in closed-loop control.
• Learning-based control formulations that provide real-time properties by design.
• Controller approximation via learning-based function approximation schemes that maintain essential controller properties.
Depending on the interests and aptitudes of the selected PhD fellow, the PhD topic can lean more in one of these directions and towards method or algorithm/computational developments.
In addition to the application in cooperation with the industry partners of the project, the institute has the opportunity to test the proposed results on demonstration platforms, such as the control of small-scale race cars
- Prof. Dr. Melanie Zeilinger (head of Intelligent Control Systems group);
- Andrea Carron (senior scientist working on learning-based control for robotics applications).
- Robert Bosch GmbH: Dr. Stefan Gering (dynamic systems control);
- Atlas Copco: Dr. Kasper Masschaele (airtec division);
- Politecnico di Milano: Prof. Dr. Lorenzo Fagiano (professor of automation and control engineering);
- University of Freiburg: Prof. Moritz Diehl (professor, head of systems control and optimization laboratory), Prof. Joschka Boedecker (professor for machine learning and neurorobotics).
Please include, in your single PDF document, the following items in this order:
- A cover letter incl. statement of research interests and career goals (max. 2 pages);
- An academic CV;
- Contact details of at least two referees incl. phone numbers and emails;
- Your diplomas and transcript of course work and grades;
- Sample of technical writing (publication or thesis);
- Proof of English language proficiency test results.
Please send your application before January 17, 2021.
Note that your PDF will be forwarded to several people in the ELO-X institutions and that in particular all Supervisory Board members of ELO-X will have access to your application material. If you want to apply to more than one ELO-X position, please create and send separate PDFs.
To be eligible, you need to be an “Early Stage Researcher” (ESR) i.e. simultaneously fulfill the following criteria at the time of recruitment:
- Nationality: you may be of any nationality.
- Mobility: you must not have resided or carried out your main activity (work, studies, etc…) in Switzerland for more than 12 months in the 3 years immediately prior to your recruitment under the ELO-X project.
- Qualifications and research experience: you must be in the first 4 years of your research career after the master degree was awarded.