School:

School of Engineering

Starting date:

1st of September or by appointment

Your role

Optimization of changing and evolving systems is a central goal in the pursuit of sustainability and efficiency of advanced manufacturing systems, which we plan to achieve with lifelong learning combined with adaptive control approaches. Incorporating predictive models and advanced control using data opens up exciting new possibilities in this domain. Our research aims to develop novel methods at the intersection of advanced control, data-driven optimization, manufacturing science and AI, to create the next generation of sustainable automation solutions for modern manufacturing systems and supply chains.

We are looking for motivated postdoctoral researcher to contribute to this effort. The envisioned research will address lifelong learning and adaptation approaches, using digital twins for continuous process optimization in industrial processes, using methods such as reinforcement learning, continual learning, Bayesian optimization and adaptive control.

The results will be demonstrated on real-world advanced manufacturing and robotic systems in collaboration with industrial and academic partners, helping to improve the efficiency and sustainability of their products.

Your goal will be to translate your own research ideas to tackle these challenges, in close collaboration with our interdisciplinary team. As part of this process, you will support our PhD, bachelor, and master students, publish in scientific journals, contribute to our teaching efforts, and participate in conferences. The position is supported by NCCR Automation and offers excellent opportunities for national and international collaboration with academic and industrial partners. The position offers good opportunity for the development of coordination and project management skills, PhD student supervision, proposal applications, and leadership skills.

The position is temporary, with up to 4 years duration. It is hosted at the ZHAW Centre for AI, Industrial AI group, supervised by Dr. Alisa Rupenyan (endowed professorship for Industrial AI at ZHAW Centre for AI), in strong collaboration with Prof. Dr. John Lygeros (heading the Automatic Control Laboratory at ETH Zurich), and Dr. Efe Balta (group leader for Advanced control and automation at inspire AG).

Your profile

You are highly motivated and dedicated with a doctoral degree in machine learning/AI, electrical, mechanical or industrial engineering, and a focus on optimization, data-driven methods for optimization and control, or probabilistic AI. You are experienced as a researcher with an active interest in manufacturing processes and in developing automation solutions to improve their efficiency and sustainability. Programming, modelling, and data analysis skills in Python will support you in contributing to our ongoing software development efforts. You are autonomous and interested in participating and managing medium-scale collaboration projects. We expect fluent English knowledge, and German would be beneficial.

This is what we stand for

Zurich University of Applied Sciences ZHAW is one of Switzerland's largest multidisciplinary universities of applied sciences, with over 14'000 students and 3'400 faculty and staff.

The School of Engineering (SoE) , as one of the leading edu-cational and research institutions in Switzerland, focuses on topics relevant to the future. 14 institutes and centres guarantee high-quality education, research and development with a focus on the areas of energy, mobility, information and health.

The Centre for Artificial Intelligence (CAI) is a Center of Excellence at ZHAW and maintains a growing number of research groups in various domains. The Industrial AI group specializes in neurosymbolic AI research for the im-provement and automation of complex manufacturing systems, combining methods from robotics, AI, and control systems.

We are looking for a deeply interested, technically skilled personality. Please honor us with a tailored cover letter and highlight facts that underline your suitability for this position, transcripts of grades from (some of) your degrees, and 2 reference contacts. We are looking forward to hearing from you!

ZHAW is committed to gender-mixed and diverse teams in order to promote equality, diversity and innovation.

What you can expect

We offer working conditions and terms of employment commensurate with higher education institutions and actively promote personal development for staff in leadership and non-leadership positions. A detailed description of advantages and benefits can be found at Working at the ZHAW . The main points are listed below:

Contact

Dr. Alisa Rupenyan
Head of Industrial AI group

Tanja Schmid
Recruiting Manager