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PhD Position on Distributed Graph Processing and Graph Partitioning at Technical University of Munich

Applicants are invited to apply for a PhD position in computer science at Technical University of Munich. This position is open until filled.

We offer a PhD Position (100 %, TVL-E 13) on the topic "Distributed Graph Processing and Graph Partitioning". This position is part of a newly started DFG funded research project that aims at developing new graph partitioning algorithms and tightly integrating them with distributed graph processing frameworks. ====

The Technical University of Munich (Technical University of Munich scholarships) (TUM) and the Alexander von Humboldt Foundation have established the Chair for Application and Middleware Systems. Our aim is to perform high-quality research in the area of distributed systems and middleware.

Graphs are a fundamental data structure and are commonly used to model relationships between data points, e.g., links between web pages, friendships between users in a social network, etc. The analysis of large graphs promises to yield to deeper insights on these graphs, e.g., about the importance of a web page or the communities in a social network. As the size of real-world graphs can easily reach billions or trillions of vertices and edges, they are processed with distributed graph processing frameworks such as Spark/GraphX or Giraph. To enable distributed processing, the graph must be partitioned, i.e., the graph is cut into a number of equally-sized components while the cut size shall be minimized. While there are many algorithms for graph partitioning available today, they fall short in several aspects. First, partitioning algorithms typically cannot exploit modern parallel hardware, such as GPGPUs, and they consume way too much memory. Second, partitioning algorithms are not tailored to the graph processing problem, i.e., it is unclear which partitioning algorithm to use as a preprocessing step to which graph processing algorithm.

To solve these issues, we are starting a DFG funded research project that aims at developing new graph partitioning algorithms and tightly integrating them with distributed graph processing frameworks. To perform this exciting research, we are looking for a highly motivated student who has recently finished his/her Master's degree in computer science. This position comes with the opportunity to obtain a PhD.

We are looking forward to your application. Please send your CV, a short motivation letter, a list of publications if applicable (also blog posts and software projects), and full transcripts of records of your B.Sc. and M.Sc. studies, all combined in one single PDF document, to ruben.mayer@tum.de. Additionally, two reference letters must be directly sent from the issuing person to ruben.mayer@tum.de. Alternatively, you can send your application by mail.

Hinweis zum Datenschutz: Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universitt Mnchen (TUM) bermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gem Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die bermittlung Ihrer Bewerbung besttigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.
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