Franz J. Schreiber
Email: mail[at]franz-schreiber[dot] (please add eu after [dot])
GitHub: github.com/FranzJS
Website: franz-schreiber.eu
Research Experience
PhD Student, Freie Universität Berlin, 2023–present
Advisor: Jens Eisert
–> Topic: Algorithms and computational resource requirements in quantum information theory.
Research Intern, Dahlem Center for Complex Quantum Systems, 2022
Mentor: Jens Eisert
–> Topic: Investigation of variational quantum learning models and their classical descriptions.
Research Intern, Freie Universität Berlin, 2021
Mentor: Frank Noé
–> Topic: Application of machine learning to coarse-graining in molecular dynamics simulations.
Research Intern, Freie Universität Berlin, 2021
Mentor: Bettina Keller
–> Topic: Investigation of path ensembles for Langevin integrators.
Research Intern, Siemens, 2020
Mentor: Holger Schererz
–> Topic: Optimization methods in complex networks.
Publications
- Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster, Franz J. Schreiber, Carlos Bravo-Prieto, A PAC-Bayesian approach to generalization for quantum models, arXiv:2603.22964 (2026)
- Franz J. Schreiber, Jens Eisert, Johannes Jakob Meyer, Tomography of Parametrized Quantum States, PRX Quantum 6, 020346 (2025)
- Franz J. Schreiber, Maximilian J. Kramer, Alexander Nietner, Jens Eisert, A measurement-driven quantum algorithm for SAT: Performance guarantees via spectral gaps and measurement parallelization, arXiv:2511.09647 (2025)
- Erik Recio-Armengol, Franz J. Schreiber, Jens Eisert, Carlos Bravo-Prieto, Learning complexity gradually in quantum machine learning models, arXiv:2411.11954 (2024)
- Franz J. Schreiber, Jens Eisert, Johannes Jakob Meyer, Classical Surrogates for Quantum Learning Models, Phys. Rev. Lett. 131, 100803 (2023)
Education
Freie Universität Berlin, 2020–2022
M.Sc. in Computational Sciences, Grade: 1.0 (highest possible)
Advisor: Jens Eisert
–> Thesis: Efficient Classical Representation of Parametrized Quantum States.
Freie Universität Berlin, 2016–2020
Studies in Mathematics and Chemistry; B.Sc. in Chemistry, Grade: 1.9
Advisor: Bettina Keller
–> Thesis: Calculation of Partition Coefficients with Molecular Dynamics Simulations.
Hermann-Billung-Gymnasium, 2008–2016
Abitur, Grade: 1.0 (highest possible)
–> Graduated top of class.
Honors and Awards
Quantum Futur Award 2023, Finalist
–> National award by the German Federal Ministry of Education and Research recognizing outstanding Master’s theses in quantum technology; selected as one of five finalists.
Teaching Experience
Teaching assistant for Mathematics I/II for Chemists and Biochemists, 2019–2022
Teaching assistant for Atomic- and Molecular Physics, 2024
Professional Activities
Journal reviewer: PRX Quantum
Conference subreviewer: QIP 2024, QTML 2025, QCTiP 2025
Co-supervision of Master’s thesis: On Quantum Algorithms for Optimization: Expected Speed-Ups and Applications by Elizaveta Patutkina, 2025
Selected Presentations
Classical surrogates for quantum learning models, QTML 2022 (extended talk)
Tomography of Parametrized Quantum States, HQCC Meeting 2024 (contributed talk)
A measurement-driven quantum algorithm for SAT: Performance guarantees via spectral gaps and measurement parallelization, QCTiP 2025 (poster)