Topic: biological neurons

Two-year postdoctoral role developing light-responsive memristor arrays to connect biological neurons with neuromorphic electronics. The project explores materials and device structures for neural imaging and closed-loop bio-hybrid systems, in collaboration with the University of Massachusetts Amherst. Based in the Nanomagnetism and Spintronics group, with access to OtaNano facilities. Gross monthly starting pay is EUR 4,229.48–4,649.25. Submit one English PDF containing a motivation letter, CV/publications, degree records and two referee contacts.

Gaute Einevoll and Mihai Petrovici discuss how neuromorphic hardware can support artificial intelligence and efficient brain simulation. They contrast high-frequency arithmetic on conventional silicon with the rich dynamics and millisecond spikes of biological neurons, and explore brain-inspired systems for emulating neural dynamics and studying computation in spiking networks. Petrovici is a senior researcher at the University of Bern. The conversation was recorded on 18 June 2026 and released on 23 September 2026; the publisher’s audio runs 1 hour, 41 minutes and 46 seconds.

We build upon and expand the efficient coding and predictive information models of neurons, presenting a novel perspective that neurons not only predict but also actively influence their future inputs through their outputs. We introduce the concept of neurons as feedback controllers of their environments, a role traditionally considered computationally demanding, particularly when the dynamical system characterizing the environment is unknown. By harnessing a novel data-driven control framework, we illustrate the feasibility of biological neurons functioning as effective feedback controllers.