PhD position: Data-driven control of industrial processes in Zürich

100%, Zurich, temporary

We invite applications for PhD positions that are part of a long-term research effort through the NCCR Automation, with the goal of demonstrating data-driven process control methods with industrial applications. The successful candidates will join the Automatic Control Laboratory at the Department of Information Technology and Electrical Engineering under the supervision of Prof. Dr. John Lygeros and Dr. Alisa Rupenyan. 

The availability and ease of integration of sensors opens the possibility of utilising additional data to monitor and control industrial processes for the optimisation of processing time and quality. The research activities within these projects will bring forward the integration of advanced control methods in combination with statistical and machine learning insights in industrial equipment. So far, such methods have mostly benefited robotic applications. Systems of increased complexity can be modelled and controlled using data-driven methods to model the systems without full knowledge of their mathematical representation. We work towards creating a data-informed automation framework that will be demonstrated on high-end industrial systems, unifying ideas from black-box adaptive control, iterative learning, and predictive control.

The research activities in this interdisciplinary field comprise several of the following activities:

• Selection of appropriate data/sensors to monitor and model the process, data collection
• Modeling and learning of a system/process model
• Adaptation or development of an appropriate control algorithm, applying an optimization-based approach
• Demonstration on the system

Data modeling, programming (Matlab, Python), and understanding of control methods are essential for the successful completion of the proposed research. Experience with integration of hardware units (Labview or C/C++ programming) could be beneficial for implementation on the real system. This type of project is a collaboration with other research labs, and possibly an industrial partner, and will be completed with the continuous support of a team of R&D experts, scientists, engineers, and doctoral students with background in mechanical, electrical, or chemical engineering.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.