neural quantum states

Application deadline: 

Monday, May 5, 2025

The development of quantum technologies and machine learning are two of the most dynamic research directions of our time. Within the Helmholtz Young Investigator Group “Machine Learning for Quantum Technology” we aspire to merge the parallel advancements of both fields, where quantum challenges match the natural strengths of machine learning and, reversely, the quantum applications call for the development of new machine learning techniques. Therefore, our research targets the exciting intersection of (non-equilibrium) quantum matter, quantum information, and machine learning with the goal of unveiling previously unexplored many-body physics and devising interactive strategies to manipulate artificial quantum systems. The Young Investigator Group is part of the Peter Grünberg Institute - Quantum Control (PGI-8) at Forschungszentrum Jülich, which specializes in novel optimal control strategies for emerging quantum technologies. Current research directions include tensor network methods, machine learning, in-situ optimal control, and quantum many-body phenomena.

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