From Integrable Probability to Disordered Systems
This international Summer School is building on three previous ZiF Summer Schools, bringing together international PhD students and young postdocs from various areas in mathematics, mathematical and theoretical physics. The participants will take part in 2 intense weeks of 8 interdisciplinary lecture series. These will be presented by 8 distinguished scientists. The school will include exercise sessions lead by the lecturers and offers the opportunity for all participants to present their own work in short contributions. The topics will include the theory of stochastic processes, complex networks, tilings, and integrable spin chains, using advanced mathematical and physics inspired tools as random matrices, partitions, replicas, and Coulomb gases. The three previous events at ZiF in 2013, 2016 and 2019 were rather successful.
Paul Bourgade (New York, USA)
Tom Claeys (Louvain, BEL)
Ioana Dumitriu (San Diego, USA)
Makoto Katori (Tokio, JPN)
Myléne Maïda (Lille, FRA)
Tomaz Prosen (Ljubljana, SLO)
Gregory Schehr (Paris, FRA)
Simone Warzel (München, GER)
Gernot Akemann, Bielefeld firstname.lastname@example.org
Friedrich Götze, Bielefeld email@example.com
In addition to accommodation and subsistance for all participants we can offer 10 stipends providing travel support. We particularly welcome applications by female participants.
Applications to participate and for travel support are welcome and should be directed to the conference centre ZiF: Ms Marina Hoffmann including a short CV and a letter of recommendation.
The deadline for requesting participation is 6th of May 2022.
There will be a participation fee of 50 Euro
For informal enquiries including the scientific part, please, contact any of the organisers.
Conference Support Service: firstname.lastname@example.org ; phone: +49 521 106-2768
The event is supported by ZiF - Zentrum für interdisziplinäre Forschung, Universität Bielefeld, Methoden 1, D-33615 Bielefeld, Germany, SFB1283 Taming uncertainty and profiting from randomness and low regularity in analysis, stochasticx and their applications.