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ETH Zürich, in the Spin Physics group, offers a four-year PhD position in Zurich focused on experimental nonlinear dynamics and nanomechanics. The project centers on building a network of Kerr parametric oscillators, studying attractor landscapes and dynamical patterns through coupled MEMS resonators and real-time measurements.
You will work closely with theory partners, run measurements, analyze data with simulations, and contribute to publications in an international setting.
PhD Position in Experimental Nonlinear Dynamics and Nanomechanics
100%, Zurich, fixed-term
We are looking for a highly motivated PhD student to join our nonlinear dynamics team. Do you have a broad interest in physics and technology? Do you like the prospect of working in an experimental project in close collaboration with theory? Are you creative, persevering, independent, and a good team player?
You can expect a cutting-edge research project that is very challenging due to the many aspects of science that are involved. For the same reason, it is a highly rewarding experience if you enjoy expanding your knowledge beyond textbook physics. We look forward to meeting you!
Is it possible to build artificial neural networks from driven nonlinear resonators? This question builds on the ideas of Hopfield and Hinton, but takes them out of equilibrium: in our resonators, a balance of continuous drive and dissipation sustains stable oscillation states. This gives us access to phenomena that are absent in equilibrium physics. For example, this may allow us to investigate how a physical network turns stored memories into dynamical patterns.
In our lab, each node is an electrical circuit or a micro-electromechanical (MEMS) resonator implementing a Kerr parametric oscillator (KPO): a driven, dissipative resonator with two stable oscillation states that act like a bit of memory. We couple several such KPOs, reading out every oscillator simultaneously and in real time. This gives us complete access to the dynamical many-body phase space. With it, we reconstruct the attractor landscape of the network, track how noise drives switching between collective states, and measure probability currents that appear when detailed balance is broken.
The central question is whether these currents organize into stable, reproducible temporal patterns and coexisting limit cycles. Networks like these bridge nonequilibrium statistical physics and neuromorphic computing, and could provide a physical route to Ising and Boltzmann machines that operate on dynamical rather than static states.
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a climate-neutral future.
Curious? So are we.
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.