The TU Berlin Database Systems and Information Management (DIMA) Group regularly offers numerous
- Bachelor’s, Master’s, Doctoral
thesis opportunities , often tied to ongoing research projects sponsored by national and international funding agencies, such as BMBF, BMWi, DFG, and the European Commission, and industry partners, such as SAP, Huawei, Amazon, Zalando, Oracle, IBM, Hewlett-Packard.
Theses typically are drawn from, but not limited to, varying domain areas including:
- Database Technology (indexing, parallel data processing, in-memory data management, transaction management, NoSQL, etc.)
- Query Processing and Optimization
- New Hardware Architectures for Information Management (Multicore/Manycore, heterogeneous CPUs/APUs, FPGA, NVRAM, SSD, etc.)
- Big Data Analytics (Flink, Hadoop, Spark, etc.)
- Large Scale Data Analysis and Data Mining (recommender systems, classification, clustering, time series analysis, machine learning)
- Information Extraction and Integration
- Business Intelligence and Data Warehousing
- Information Retrieval and Search Engines
- Cloud Computing and Data as a Service (DaaS)
- Applications of Information Systems
DIMA thesis opportunities provide students with challenging research problems and enable them to collaborate with national and international research partners. Theses are typically written in English. However, some are written in German.
Typically, students are required to possess:
- outstanding programming skills in C++, Java, or Scala,
- extensive knowledge in database systems, such as in IBM DB2 or Oracle, or big data analytics systems such as Flink, Hadoop, Spark
- basic knowledge of an IDE (Eclipse, IntelliJ) and Version control (SVN, Git or both).
please, visit the Open Theses  page and contact the corresponding thesis supervisor via email. Alternatively, contact a Senior Researcher via email to either propose your own thesis topic or explore another thesis topic tied to ongoing research at DIMA.
In order to conduct a Bachelor thesis, the ideal student will have successfully completed undergraduate coursework , such as the introduction to database systems (i.e., ISDA, former MPGI5), and the database lab course (i.e., DBPRA), as well as a seminar (i.e., DBSEM) or a project (i.e., DBPRO) or advanced bachelor courses such as data warehousing and business intelligence (DW)
Master students ideally have completed the introductory graduate course , database lab course (IDBPRA) and advanced courses, such as scalable data analysis and data mining (AIM3), the big data analytics project (BDAPRO), readings in database systems seminar (BDASEM). Depending on the thesis topic, additional knowledge in compiler technology, natural language processing, networking, distributed systems, embedded systems, or machine learning may be useful or required.