Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.
We invite applications for several PhD positions that are part of a larger research program with the goal of enabling learning in high performance control systems that are safety-critical.
The successful candidates will join the Institute for Dynamic Systems and Control at the Department of Mechanical and Process Engineering at ETH Zürich under the supervision of Prof. Melanie Zeilinger.
Automation is playing an increasingly important role in our daily lifes. An opportunity that is transforming how control systems work is the availability of sensing, computation and communication allowing control systems to collect, process and exchange information. While learning methods have seen tremendous succes in various domains in recent years, their application to control systems is severely limited by safety concerns.
Our research develops the theory, methods and tools for safe learning in dynamical control systems. We address the problem by a systematic combination of control theory, learning and optimization techniques. While method development is in the focus, we also demonstrate the results in a number of different applications, ranging from robotics, or manufacturing systems to space and biomedical applications.
The PhD position will lie in the general context of Safe Learning in Control and will focus on a selection of the following challenges:
Our PhD projects involve a mix of theory, computational tools and demonstrating applications. The particular PhD project and emphasis will be selected for the individual candidate.
The PhD student can expect a full-time position in a highly motivated and small research team offering an excellent research infrastructure and environment.
We are looking for a candidate with a Master’s degree from a recognized university (or close to completion) with an excellent GPA; strong analytical skills and background in systems and control; some experience in machine learning and optimization is beneficial but not a prerequisite. Proficient oral and written English skills are expected.
We look forward to receiving your online application with the following documents: CV, statement of objectives and research interests (1-2 pages), transcripts of all degrees obtained (in English), names and contact information of three references and one publication (thesis/paper). Please note that we only accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about us can be found on our website .
29-02-2024
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