Are you excited about developing new mathematical foundations for energy-efficient computing? Do you want to contribute to cutting-edge research at the intersection of systems and control theory, optimization, circuit theory, and neuromorphic computing?
The University of Groningen is seeking a highly motivated PhD candidate to work on a fundamental research project on systems and control theory for learning in neuromorphic circuits. Neuromorphic computing is an analog, brain-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development and analysis of dedicated algorithms for training analog circuits directly from data.
In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and dissipative networks. We will view learning as a feedback interconnection of continuous-time (circuit) dynamics and an optimization algorithm. The key idea is to develop algorithms that minimise cost functions inspired by notions of energy, leading to highly efficient, local learning rules.
What are you going to do?
As a PhD candidate, you will develop mathematical theory for learning in nonlinear and dynamic circuits. Building on preliminary results for resistive circuits, you will study circuits containing memristive and capacitive elements, as well as more general dissipative networks. The project combines systems and control theory, circuit theory, optimization, and machine learning, with the ultimate goal of advancing the mathematical foundations of physics-based learning.
Your responsibilities include:
- Developing a system-theoretic framework that models learning as the feedback interconnection between continuous-time circuit dynamics and optimization algorithms.
- Designing novel energy-based learning algorithms for training analog circuits directly from input-output data.
- Developing fully decentralised learning rules that rely on local circuit information and are suitable for large-scale systems.
- Establishing rigorous theoretical guarantees for convergence and scalability of the proposed learning algorithms.
- Extending the theory from analog circuits to more general dissipative networks.
- Testing and validating the developed methods.
- Publishing research findings in leading international journals and conferences and presenting your work at scientific meetings.
- Contributing to teaching activities and supervising Bachelor's and Master's students where appropriate.
Requirements
We are looking for an enthusiastic researcher who enjoys solving challenging problems and working in an international research environment.
You should have:
- A Master's degree in Systems and Control, (Applied) Mathematics, Electrical Engineering, or a closely related field.
- A strong mathematical background and an interest in conducting theoretical research.
- Excellent English communication skills, both written and spoken.
- Strong analytical abilities, creativity, persistence, and the ability to collaborate effectively.
- Familiarity with circuit theory, networked systems, machine learning, or neuromorphic computing is considered an advantage, but is not required.
Conditions of employment
What can you expect from us?
- 232 vacation hours per year, based on a 38-hour workweek (1.0 FTE). You can also work more or fewer hours in exchange for more or fewer free hours. For example, with a 40-hour workweek, you save 96 extra free hours, and with a 36-hour workweek, you lose 96 hours.
- End-of-year bonus of 8.3% and 8% holiday allowance.
- Extensive opportunities for personal and professional development.
Employer
University of Groningen
At the University of Groningen (UG), researchers from all fields of academia and technology are working on academic challenges and societal questions. Lecturers prepare their students for meaningful careers within or outside the academic world. Interdisciplinary research and teaching, sharing of knowledge, collaboration with businesses, government institutions, and societal organizations are aspects that are of the utmost importance to this European top university. The UG aims to be an open academic community with an inclusive and safe working climate that invites you to add your value.
Department
Faculty of Science and Engineering
The Faculty of Science and Engineering (FSE) provides teaching and research across a wide range of disciplines, from physics and biology to artificial intelligence, mechanical engineering, and pharmacy. In close collaboration with partners from industry, healthcare, and society, we contribute to the urgent challenges of our time, such as energy, sustainability, digitization, and medical technology. Our community is open and informal, with more than 7,000 students, 1,000 PhD students, and 1,400 staff members from all over the world. If you would like to learn more about the Faculty of Science and Engineering, visit rug.nl/fse.
The successful candidate will join the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence within the Faculty of Science and Engineering at the University of Groningen.
The research will be carried out in the Systems, Control and Optimization Group. Our group is part of the Jan C. Willems Center for Systems and Control that unites the different control groups in Groningen. This is a leading center (ranked first in the EU (fourth in Europe) according to the 2024 Shanghai Ranking). The successful candidate will benefit from connections within the center, as well as regular seminars, joint group meetings, and interaction with other PhD students and postdocs in a lively and supportive environment.
The PhD project is embedded within the European Research Council (ERC) Starting Grant project “Energy-based learning of complex dynamical systems” (E-BLOCS), led by Dr. Henk van Waarde. The PhD student will actively work together with the other members of the project, and also has many opportunities for international collaboration, research visits, and interdisciplinary training.
Additional information
Do you have any questions or need more information?
Questions about the content of the job?
Henk van Waarde (Assistant Professor): H.J.van.Waarde@rug.nl
Questions about your application process?
Henk van Waarde (Assistant Professor): H.J.van.Waarde@rug.nl
Working at University of Groningen
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