Postdoctoral Position in Automated Scientific Discovery, Computational Quantum Many-Body Physics, and Machine Learning
The Quantum AI lab at ETH Zürich, led by Prof. Juan Carrasquilla, is seeking postdoctoral researchers to work at the intersection of computational quantum many-body physics, automated scientific discovery, and machine learning. This position offers the opportunity to contribute to the second quantum revolution, where machine learning is increasingly used to explore complex quantum systems, with significant implications for materials science, quantum chemistry, and quantum technology. The lab's long-term goal is to extend the applicability of machine learning to solve critical problems in quantum many-body physics, impacting condensed matter theory, quantum materials, and beyond. As a postdoctoral researcher, you will address fundamental questions such as simulating strongly correlated quantum systems using both classical and quantum computing resources and automating the scientific process to enable new breakthroughs. The role involves engaging with a diverse array of concepts at the intersection of artificial intelligence, condensed matter physics, and quantum computing. The position is full-time, with flexible starting dates in 2025 and 2026. Applicants should have a PhD in quantum physics, computer science, or applied mathematics, and a strong interest in developing theoretical or computational methods for quantum many-body systems, quantum computing, or machine learning. Leadership skills, the ability to collaborate with a diverse group, and the capacity to work independently and in teams are essential. Experience with large language models and automation is desirable. The lab offers a supportive environment, opportunities for internal and international collaboration, mentoring of students and interns, access to state-of-the-art computational facilities, and travel to conferences. ETH Zürich is a world-leading university in science and technology, known for its commitment to diversity, sustainability, and excellence in research and education. Applications should be submitted online, including a CV, research statement, and contact information for at least two referees. The review of applications begins immediately and continues until the positions are filled. For further information, contact Prof. Juan Carrasquilla at [email protected] (no applications via email).