PhD or PostDoc Position (100 %, TVL-E 13) on "Graph Data Systems" at TUM Campus Heilbronn

09.06.2022, Wissenschaftliches Personal

As part of an initiative by the community service foundation Dieter Schwarz Foundation (DSF), TUM created a teaching and research facility on the Bildungscampus Heilbronn (Heilbronn Education Campus). TUM Campus Heilbronn focuses on the areas of managing digital transformation, family businesses, and computer science.

Requirements
- Master’s degree in computer science with very good results
- Interest on topics around the area of distributed systems and data management
- Basic knowledge in distributed systems and graph algorithms is desired
- Hand-on experience with large-scale data analytics frameworks (Hadoop, Spark, Flink, 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
- This position is located on the new Heilbronn campus (not in Garching / Munich!)

Your tasks
Graphs are a fundamental data structure and are commonly used to model relationships between data points such as links between web pages or friendships between users in a social network. Due to the large variety in data science tasks performed with graph-structured data, different specialized systems have been developed, such as graph processing frameworks, graph databases, graph learning frameworks, knowledge graph systems, and graph mining systems. While each of them is specialized on a specific type of task and is highly efficient for it, maintaining and integrating a zoo of graph data systems is a huge challenge and leaves a lot of room for optimizations.

Our vision is to explore opportunities to unify core parts of the different types of systems and develop a core graph data system that can serve as a common building block. This way, redundancies in keeping multiple cop-ies of graph data in different systems could be reduced, maintenance of the systems could be improved, and operational costs could be optimized. To perform this exciting research, we are looking for a highly motivated student or PostDoc who has recently finished his/her Master’s degree or PhD degree in computer science.

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)
- 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 encour-age 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 [email protected].

Tel. +49 (89) 289 – 18486
[email protected]

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: [email protected]