The NanoComputing Research Lab
in Integrated Circuits (IC) group within the Department of Electrical Engineering of the Eindhoven University of Technology (TU/e) is a leading research group at the forefront of interdisciplinary studies, specializing in the intersection of physics, information theory, and computing. We are currently seeking a highly skilled and motivated Research Scientist to join our dynamic team and contribute to a cutting-edge project that formalizes the synergy between physics, information theory, and machine learning, particularly focusing on computing with Oscillatory Neural Networks (ONNs).Project
The project aims to formalize the synergies between physics, information theory, and machine learning to enhance computing capabilities with ONNs. Inspired by Hopfield neural networks, ONNs represent a bridge between physics and machine learning, demonstrating emergent computational properties through the dynamics of coupled oscillators. The successful candidate will rigorously investigate the link between statistical physics, the theory of learning, and computing with ONNs. The computation model of ONNs, described through the Ising model, will also be a focal point for mapping and solving combinatorial optimization problems. The project will extend into practical applications, addressing challenges in weather forecasting and optimization problems such as the traveling salesman problem and the determination of 3D protein structures.Candidate
We seek an enthusiastic and dynamic candidate with a Ph.D. in Physics, Machine Learning, or a related field, demonstrating a deep passion for interdisciplinary research. The ideal candidate will possess proven expertise in machine learning and physics complemented by a solid background in mathematics and computational physics. With a track record of engaging in interdisciplinary projects, the candidate should showcase the ability to bridge theoretical concepts from physics and information theory to practical applications in machine learning. Strong analytical and problem-solving skills are essential, reflecting a keen interest in formalizing connections between statistical physics, learning theories, and computing with oscillatory neural networks.