In the week of 29 November – 4 December 2026 we are going to hold the 1st Winter School for PhD and Master Students at the Max Planck Institute for the Science of Light, Erlangen.
Application Details #
- Deadline: September 30, 2026
- Registration Fee: Free, but approval is required.
- Website & Application: https://indico.mlcqs.de/event/1/
- Contact: For inquiries, contact Ms. Julia Stier at julia.stier@verwaltung.uni-regensburg.de
Accommodation #
Participants are expected to book their own travel and accommodation. Do NOT book your travel and accommodation before your application has been approved!
The following list of hotels may serve as a guideline:
About the School & Tracks #
Are you fascinated by the intersection of artificial intelligence and quantum physics? This specialized school invites PhD and Master students to explore cutting-edge machine learning techniques applied to complex quantum systems. Organized as part of the Research Unit FOR 5919, the program combines theoretical lectures with comprehensive hands-on coding tutorials to bridge foundational concepts with active research.
Participants choose one of two specialized tracks during Days 2–4:
- Track 1 (Neural Quantum States): Focuses on representing complex many-body wave functions using neural network architectures, variational Monte Carlo, and ground state searches. No prior NQS knowledge is required!
- Track 2 (Reinforcement Learning for Quantum Tech): Covers RL fundamentals, strategies for quantum control optimization, quantum error correction protocols, and quantum circuit dynamics. No prior RL knowledge is required!
Program Schedule & Logistics #
- Phase 1 (Nov 30, 1:30 PM Kick-off): Introduction to deep learning, neural network architectures, and optimization.
- Phase 2 (Dec 1–3): Intensive track-specific lectures and interactive track-oriented hands-on programming tutorials.
- Phase 3 (Dec 4, Ends 12:30 PM): Joint scientific session featuring contemporary research talks.
Prerequisites: A basic understanding of quantum mechanics and Python proficiency are expected; no prior machine learning experience is needed.
Equipment Required: Participants must bring their own laptops for the hands-on numerical and coding sessions.
Lecturers #
NQS Track
- Annabelle Bohrdt (LMU Munich)
- Markus Heyl (Univ. of Augsburg)
RL Track
- Florian Marquardt (MPL Erlangen)
- Marin Bukov (MPI-PKS Dresden)
