Fulltime Position, TV-L E 13 PhD Position on Distributed Graph Processing and Graph Partitioning 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. About us The Technical University of Munich (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. Requirements - Master's degree in computer science with very good results - Interest in topics around the area of distributed systems, graph processing, Big Data - Previous knowledge in distributed systems is desired - Hand-on experience with large-scale data analytics frameworks (Hadoop, Spark, Flink, etc.) is desired - Experience with parallel programming / GPGPU programming (CUDA, OpenCL, etc.) is desired - Interest in the development of software systems, very good knowledge and skills in programming with standard programming languages such as C++ or Java - Excellent command of English - Very good writing skills - High engagement, high motivation, pro-active communication skills, and high social skills Your tasks 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 offer - You work in a highly innovative environment - Technical supervision at one of the leading universities of Germany - Employment as a research associate (TVL-E13) in a fulltime position (fixed-term contract) - Funds for travel and student helpers (HiWis) is available from the project. - Disabled persons will be preferred at the same level of suitability to the position. - The Technical University of Munich seeks to increase the proportion of women. Hence, we explicitly encourage women to apply to this position. - We will consider all incoming applications until the position is filled. Application 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. Technische Universität München Lehrstuhl für Anwendungs- und Middlewaresysteme Boltzmannstrasse 3, 85478 Garching, Germany Tel. +49 (89) 289 – 18486 ruben.mayer@tum.de http://www.i13.in.tum.de Hinweis zum Datenschutz: Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben. Kontakt: Ruben Mayer (ruben.mayer@tum.de) If you apply for this position please say you saw it on Engineeroxy

Fulltime Position, TV-L E 13

PhD Position on Distributed Graph Processing and Graph Partitioning

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.

About us

The Technical University of Munich (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.

Requirements

- Master's degree in computer science with very good results
- Interest in topics around the area of distributed systems, graph processing, Big Data
- Previous knowledge in distributed systems is desired
- Hand-on experience with large-scale data analytics frameworks (Hadoop, Spark, Flink, etc.) is desired
- Experience with parallel programming / GPGPU programming (CUDA, OpenCL, etc.) is desired
- Interest in the development of software systems, very good knowledge and skills in programming with
standard programming languages such as C++ or Java
- Excellent command of English
- Very good writing skills
- High engagement, high motivation, pro-active communication skills, and high social skills

Your tasks

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 offer

- You work in a highly innovative environment
- Technical supervision at one of the leading universities of Germany
- Employment as a research associate (TVL-E13) in a fulltime position (fixed-term contract)
- Funds for travel and student helpers (HiWis) is available from the project.
- Disabled persons will be preferred at the same level of suitability to the position.
- The Technical University of Munich seeks to increase the proportion of women. Hence, we explicitly encourage women to apply to this position.
- We will consider all incoming applications until the position is filled.

Application

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.

Technische Universität München
Lehrstuhl für Anwendungs- und Middlewaresysteme
Boltzmannstrasse 3, 85478 Garching, Germany
Tel. +49 (89) 289 – 18486
ruben.mayer@tum.de
http://www.i13.in.tum.de

Hinweis zum Datenschutz:

Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.

Kontakt: Ruben Mayer (ruben.mayer@tum.de)

If you apply for this position please say you saw it on Engineeroxy

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