Doctoral (PhD) Student Positions in Control and Learning Theory
The Automatic Control Laboratory at ETH Zurich is a community of researchers from over 20 countries working on automation methods. We are looking for two doctoral students to contribute to our research efforts in control theory and learning methods.
The laboratory works closely with the National Centre of Competence in Research (NCCR) Automation, fostering collaboration among Swiss researchers in automatic control, optimisation, and machine learning. Our activities support our researchers in expanding their interests and skills beyond research.
Project Background
Control theory underlies the drive towards automation. As systems become larger and more complex, control methods dealing with uncertainty have become increasingly important. This has led to a rapprochement between control theory and machine learning. The two doctoral student positions aim to explore this interplay.
We seek motivated doctoral students to contribute to this effort. The envisioned research will address:
1. Distributionally robust Markov Decision Processes: This approach aims to extend distributional robustness to different types of uncertainty descriptions and infinite state-action MDP.
2. Policy gradient for control parametrisations: This involves extending policy gradient methods to design policies based on control architectures.
We envision testing the methods on benchmark problems, robotic testbeds, and real-world applications including energy systems, industrial processes, and mobility.
Profile
You have a Master's degree in a field addressing control theory, electrical or mechanical engineering, or applied mathematics. Programming, modelling, and data analysis skills in Python and machine learning/optimization libraries/toolboxes support you in contributing to our ongoing software development efforts. Your English skills help you navigate our international environment.
We Offer
We offer a multifaceted position in a modern research environment with excellent infrastructure.
ETH Zurich encourages an inclusive culture, promoting equality of opportunity, valuing diversity, and nurturing a working and learning environment respecting the rights and dignity of all staff and students.
Application Process
We look forward to receiving your application including a short statement of research interests, CV, one publication/thesis, and transcripts of all degrees.
Please submit all information as a single merged PDF file through the online application portal.
The positions remain open until filled. Applications received by 31 March 2025 will receive full attention.