**Job Description:**
We are seeking highly motivated postdoctoral researchers to contribute to our cutting-edge research effort.
1. Lifelong Learning and Adaptation: Develop digital twin-based methods for continuous process optimization in industrial processes, leveraging techniques such as reinforcement learning, continual learning, Bayesian optimization, and adaptive control.
2. Digital Twin-Based Learning and Optimization: Design and implement advanced machine learning, federated learning, and optimization methods for manufacturing processes like 3D Printing, laser cutting, precision motion, and robotic manipulation.
Your work will be applied to real-world advanced manufacturing and robotic systems in collaboration with industry partners, enhancing the efficiency and sustainability of their products.
You will translate your own research ideas into impactful solutions, working closely with our interdisciplinary team. As part of this, you will support master students, publish research in scientific journals, contribute to teaching efforts, and participate in conferences.
This opportunity is supported by the NCCR Automation and the European Project DMaaST, providing excellent prospects for national and international collaboration with academic and industrial partners.
Requirements:
* Ph.D. in electrical, mechanical, or industrial engineering
* Experience as a researcher with a passion for manufacturing processes and automation solutions
* Proficiency in Python for programming, modeling, and data analysis
* Strong English language skills for effective communication within our international environment
About Our Team:
We value innovative thinking, collaboration, and dedication to advancing the field of automation. If you are a motivated individual with a strong background in engineering and research, we encourage you to apply.