Post Doc in Machine Learning and Data Analytics

Ludwig Maximilians University of Munich

PostDoc in the area of Machine Learning and Data Analytics (f/m/d)

Institution: Faculty of Mathematics, Computer Science and Statistics
(Institute for Computer Science, Chair for Database Systems and Data Mining)

Occupation date: As soon as possible

Application deadline: December 16, 2020

Salary group: E14

Time limit: December 31, 2022

There is basically the possibility of part-time employment.

The Ludwig Maximilians University of Munich (LMU) is one of the most renowned and largest universities in Germany.


Our team advances data science, data mining, machine learning, artificial intelligence and data-base technologies in our research and teaching activities. We aim at better supporting the analy-sis of huge and complex data sets from various domains including engineering, business, hu-manities, life sciences, among others.

We are looking for talented and highly motivated computer scientists (or people with a related background) interested in the design, development, and analysis of novel machine learning methods. The positions are situated within the Munich Center for Machine Learning (MCML), one of the national competence centers for Machine Learning in Germany and are expected to focus on the following topics:

• Unsupervised Learning / Clustering
• Process Mining
• Reinforcement Learning
• Machine Learning on Graphs
• Active Learning

Your tasks:

• Independent research in cooperation with internal and external partners
• Publishing research results in form of peer-reviewed articles on relevant confer-ences/journals
• Scientific supervision of current and contribution to acquisition of future research projects
• Supervision of scientific staff and Master/Bachelor students
• Participation in other scientific tasks of the chair, e.g. contributing to design decisions for infrastructure
• Contributing to the teaching activities of the chair, comprising lectures, seminars, practical courses, exercises in the Bachelor and Master programs in Computer Science

Our offer:

We offer you an interesting and responsible workplace with good opportunities for further train-ing and development. Your workplace is centrally located in Munich and can be easily reached by public transport. Classification is according to TV-L, pay group 14. The position is provision-ally limited until 31.12.2022. Part-time employment is generally possible. LMU Munich is inter-ested in increasing the number of female employees and encourages women to apply. Severely handicapped persons are given preference if they are otherwise essentially equally suitable.


Your profile:

• Completed university degree with Ph.D. in the corresponding area and publications at top conferences including the following venues: KDD, ICDM, NeurIPS, ICML, BPM, ICLR, WWW, AAAI, IJCAI, etc.
• Strong background in machine learning / data mining
• Strong programming skills in at least one programming language (preferably Python and with experience in TensorFlow, PyTorch or similar)
• Good English language skills (your responsibilities include to write publications and to give international presentations)
• Knowledge of German is an asset, but not a must (e.g. participation in national conferences)

Ihr Arbeitsplatz befindet sich in zentraler Lage in München und ist sehr gut mit öffentlichen Verkehrsmitteln zu erreichen. Wir bieten Ihnen eine interessante und verantwortungsvolle Tätigkeit mit guten Weiterbildungs- und Entwicklungsmöglichkeiten. Schwerbehinderte Personen werden bei ansonsten im Wesentlichen gleicher Eignung bevorzugt. Die Bewerbung von Frauen wird begrüßt.


Ludwig-Maximilians-Universität München,
Institut für Informatik
Lehrstuhl für Datenbanksysteme und Data Mining
Prof. Dr. Thomas Seidl
Oettingenstr. 67
80538 München

Please send your meaningful application documents until 16.12.2020 by mail (single PDF, max. 5MB; no links to external files; in English or German) by mail or email. with subject “PostDoc Application”. The application should include a brief statement of interest/motivation letter, a summary/abstract of the doctoral thesis, and a list of publications. A list of references (names, contact information) is helpful as well.


Prof. Dr. Thomas Seidl
+49 89 2180-9191

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