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.

• Investigate the theoretical formalisms between statistical physics, learning, and computing with ONNs.
• Utilize the Ising model to deepen the understanding of physical learning and self-organization in ONNs.
• Apply findings to address real-world challenges in weather forecasting and combinatorial optimization.
• Collaborate with a multidisciplinary team to advance the project's objectives.
• Mentor and provide support to junior team members.

Qualifications:

• Ph.D. in Physics, Machine Learning, or a related field.
• Expertise in machine learning, physics, and graph theory.
• Background in mathematics and computational physics is highly desired.
• Proven research experience in interdisciplinary projects.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Excellent programming skills and proficiency in relevant software tools.

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for one year in a research group with an excellent reputation, with an intermediate evaluation after one year for extension.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. €3,877 max. €5,090).
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Teamis available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.