The Department of Informatics (https://www.in.tum.de) at Technical
University of Munich (TUM) invites applications for PhD/researcher
positions in the area of Machine Learning / Data Science at the research
group Data Mining and Analytics (www.kdd.in.tum.de).
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. Particularly, we are
currently offering positions focusing on the following topics:
* robust and adversarial machine learning
* transfer learning
* anomaly and outlier detection in event and sequence data
* machine learning for graphs
The developed methods will be applied and evaluated in various domains
such as the natural sciences (e.g., molecular graphs), the field of
engineering (sensor and diagnosis signals), and the web (e.g., social
networks, knowledge graphs). Some of the positions are supported by the
BMW AG and, thus, offer the opportunity for close collaborations in the
field of machine learning in the automotive industry.
** Candidate skills & profile **
* University degree (M.Sc.) with very good grades in Computer Science or
related fields
* Strong background in machine learning / data mining
* Strong programming skills in at least one programming language
(preferably Python)
* 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)
** How to apply? **
Please send your application (in a single file in pdf format; in English
or German) by email to Prof. Stephan Günnemann (guennemann@in.tum.de;
subject: PhD Application). The application should include a brief
statement of interests/motivation letter, a curriculum vitae, copies of
certificates, a summary/abstract of the master thesis, and (if already
available) a list of publications.
Salary is according to the level TV-L E 13 of the German public sector.
As part of the Excellence Initiative of the German federal and state
governments, TUM has been pursuing the strategic goal of substantially
increasing the diversity of its faculty. As an equal opportunity and
affirmative action employer, TUM explicitly encourages nominations of
and applications from women as well as from all others who would bring
additional diversity dimensions to the university’s research and
teaching strategies. Preference will be given to disabled candidates
with essentially the same qualifications.
Applications will be considered as they are received and until the
positions are filled. Please check our website for up to date
information: http://www.kdd.in.tum.de/open-positions/
For further information, please do not hesitate to contact Prof. Stephan
Günnemann (guennemann@in.tum.de).