PhD in (Applied/Engineering) Physics

Electrification and digitalisation are among the major areas for the future transition to sustainable societies. The Department of Electrical Engineering conducts successful research and education in these areas - including renewable energy sources, electric vehicles, industrial IoT, 6G communication, and wireless sensor networks, as well as research and education in Life Science, health technology, smart electronic sensors, and medical systems. The Department of Electrical Engineering is an international environment with around 160 employees who contribute to important technological energy and health at the Ångström Laboratory./nWe are now looking for a PhD student in Neuromorphic Devices and Circuits for next-generation sensing and computing./nThe position is placed at the Division of Solid-State Electronics, within the Department of Electrical Engineering. Here you will find a welcoming working environment with an active doctoral student network and a variety of experimental projects. The division collaborates with Swedish companies – both public and private – as well as other stakeholders within the various research areas./nProject description:/nHuman brains can process complex, dynamic, and real-time information with remarkable efficiency after millions of years of evolution. Neuromorphic computing, inspired by how the human brain functions, offers a promising solution to dramatically lowering power consumption and enables fast and adaptive information processing in today’s Zettabyte-scale data era. Artificial neurons and synapses are the core building blocks of neuromorphic systems. Yet currently, these neuromorphic circuits still fall far short of the efficiency and functionality of their biological counterparts./nThis project aims to overcome these limitations through a synergistic circuit–device co-design that jointly optimizes both circuit architectures and component properties, ensuring that intrinsic device physics effectively translate into significant system-level improvements. In this project, we will develop neuromorphic devices with inherent biological resemblance and compact, low-power neuromorphic circuits. We will also simulate high-efficiency spiking neural networks (SNN) and build neuromorphic sensory systems to validate performance and explore broad biomedical and other potential applications. The outcomes will contribute fundamental knowledge and new technologies that move us closer to sensing and computing systems approaching the efficiency of the human brain./nThis project involves both experimental development and theoretical modelling. Therefore, it requires the candidate to have a solid background in physics, electronics, and mathematics, along with strong practical experimental skills./nWe have an exciting research environment shaped jointly by the doctoral student and the research team. The doctoral student will be supervised by at least two supervisors and will carry out the project within a multidisciplinary setting where scientists of complementary backgrounds collaborate.