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Technische Universität München
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  • Team
    • Stephan Günnemann
    • Sirine Ayadi
    • Tim Beyer
    • Jonas Dornbusch
    • Eike Eberhard
    • Dominik Fuchsgruber
    • Nicholas Gao
    • Simon Geisler
    • Lukas Gosch
    • Filippo Guerranti
    • Leon Hetzel
    • Niklas Kemper
    • Amine Ketata
    • Marcel Kollovieh
    • Anna-Kathrin Kopetzki
    • Arthur Kosmala
    • Aleksei Kuvshinov
    • Richard Leibrandt
    • Marten Lienen
    • David Lüdke
    • Aman Saxena
    • Sebastian Schmidt
    • Yan Scholten
    • Jan Schuchardt
    • Leo Schwinn
    • Johanna Sommer
    • Tom Wollschläger
    • Alumni
      • Amir Akbarnejad
      • Roberto Alonso
      • Bertrand Charpentier
      • Marin Bilos
      • Aleksandar Bojchevski
      • Johannes Gasteiger, né Klicpera
      • Maria Kaiser
      • Richard Kurle
      • Hao Lin
      • John Rachwan
      • Oleksandr Shchur
      • Armin Moin
      • Daniel Zügner
  • Lehre
    • Sommersemester 2025
      • Advanced Machine Learning: Deep Generative Models
      • Applied Machine Learning
      • Seminar: Selected Topics in Machine Learning Research
      • Seminar: Current Topics in Machine Learning
    • Wintersemester 2024/25
      • Machine Learning
      • Seminar: Selected Topics in Machine Learning Research
      • Seminar: Current Topics in Machine Learning
    • Sommersemester 2024
      • Machine Learning for Graphs and Sequential Data
      • Advanced Machine Learning: Deep Generative Models
      • Applied Machine Learning
      • Seminar: Selected Topics in Machine Learning Research
    • Wintersemester 2023/24
      • Machine Learning
      • Applied Machine Learning
      • Seminar: Selected Topics in Machine Learning Research
      • Seminar: Machine Learning for Sequential Decision Making
    • Sommersemester 2023
      • Machine Learning for Graphs and Sequential Data
      • Advanced Machine Learning: Deep Generative Models
      • Large-Scale Machine Learning
      • Seminar
    • Wintersemester 2022/23
      • Machine Learning
      • Large-Scale Machine Learning
      • Seminar
    • Sommersemester 2022
      • Machine Learning for Graphs and Sequential Data
      • Large-Scale Machine Learning
      • Seminar (Selected Topics)
      • Seminar (Time Series)
    • Wintersemester 2021/22
      • Machine Learning
      • Large-Scale Machine Learning
      • Seminar
    • Sommersemester 2021
      • Machine Learning for Graphs and Sequential Data
      • Large-Scale Machine Learning
      • Seminar
    • Wintersemester 2020/21
      • Machine Learning
      • Large-Scale Machine Learning
      • Seminar
    • Sommersemester 2020
      • Machine Learning for Graphs and Sequential Data
      • Large-Scale Machine Learning
      • Seminar
    • Wintersemester 2019/20
      • Machine Learning
      • Large-Scale Machine Learning
    • Sommersemester 2019
      • Mining Massive Datasets
      • Large-Scale Machine Learning
      • Oberseminar
    • Wintersemester 2018/19
      • Machine Learning
      • Large-Scale Machine Learning
      • Oberseminar
    • Sommersemester 2018
      • Mining Massive Datasets
      • Large-Scale Machine Learning
      • Oberseminar
    • Wintersemester 2017/18
      • Machine Learning
      • Oberseminar
    • Sommersemester 2017
      • Robust Data Mining Techniques
      • Efficient Inference and Large-Scale Machine Learning
      • Oberseminar
    • Wintersemester 2016/17
      • Mining Massive Datasets
    • Sommersemester 2016
      • Large-Scale Graph Analytics and Machine Learning
    • Wintersemester 2015/16
      • Mining Massive Datasets
    • Sommersemester 2015
      • Data Science in the Era of Big Data
    • Machine Learning Lab
  • Forschung
    • Robust Machine Learning
    • Machine Learning for Graphs/Networks
    • Machine Learning for Temporal and Dynamical Data
    • Bayesian (Deep) Learning / Uncertainty
    • Efficient ML
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News

Open position: Student assistant for MMDS lecture

29.11.2016


We are currently offering student assistant positions (Hiwi/Tutor) for our lecture on Mining Massive Datasets. More details are available here.


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Informatik 26 - Data Analytics and Machine Learning


Prof. Dr. Stephan Günnemann

Technische Universität München
TUM School of Computation, Information and Technology
Department of Computer Science
Boltzmannstr. 3
85748 Garching 

Sekretariat:
Raum 00.11.057
Tel.: +49 89 289-17256
Fax: +49 89 289-17257

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