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PostDoc – https://stellenticket.de/77576/TUB/?lang=en
PhD – https://stellenticket.de/77572/TUB/?lang=en
———-Vision
The Berlin Center for Machine Learning (BZML, Berliner Zentrum für Maschinelles Lernen) aims at the systematic and sustainable expansion of interdisciplinary machine learning research, both in proven research constellations as well as in new, highly topical scientific objectives that have not yet been jointly researched.
The efficient utilization of a priori knowledge in learning processes and the investigation of the effects of erroneous or incomplete data are crucial to this mission. In parallel, BZML experts further develop techniques for interpreting and explaining complex learning methods in order to arrive at more robust and, above all, more trustworthy models. Only then can statistical models be used to solve challenging scientific problems. In particular, the requirements and statistical peculiarities from the application areas biomedicine, digital humanities and communication are central to the BZML.
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Talks
Management

Klaus-Robert Müller
TU BerlinDirector of the Berlin Center for Machine Learning

Volker Markl
TU BerlinCo-Director of the Berlin Center for Machine Learning
Principal Investigators

Gilles Blanchard
University of Potsdam
Giuseppe Caire
TU Berlin
Tim Conrad
FU Berlin, Zuse Institut Berlin
Gerd Graßhoff
HU Berlin
Anja Hennemuth
Charité Berlin
Frederick Klauschen
Charité Berlin
Titus Kühne
Charité Berlin
Gitta Kutyniok
TU Berlin
Grégoire Montavon
TU Berlin
Uwe Ohler
Max Delbruck Center
Manfred Opper
TU Berlin
Jürgen Renn
Max Planck Institute for the History of Science Berlin
Wojciech Samek
Fraunhofer Heinrich Hertz Institute
Christof Schütte
FU Berlin, Zuse Institut Berlin
Vladimir Spokoiny
Weierstrass Institut Berlin
Slawomir Stanczak
TU Berlin
Matteo Valleriani
Max Planck Institute for the History of Science, Berlin
Martin Vingron
Max Planck Institute for Molecular Genetics
Thomas Wiegand
Heinrich-Hertz-Institut, TU BerlinAssociated Investigators

Roland Schwarz
Max Delbruck Center