A position to implement a Time Series Management System(TSMS) to be used in 6G network infrastructure is available at the Data Engineering, Science and Systems(DESS) group at the Department of Computer Science at Aalborg University(AAU), Denmark. The position is available for a flexible starting date as soon as possible after 1st November 2024. The position is initially for 2 years, with the possibility of extension up to 4 years in total after mutual consent.

About the Data Engineering, Science and Systems(DESS) group: DESS research focuses on data-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and intelligent transport. International evaluations place DESS in the global top tier. For example, csrankings.org lists DESS as no. 1 in Europe and no. 9 in the world within Databases for the period 2023-2024. More information about DESS can be found at:https://www.cs.aau.dk/research/Data-Engineering-Science-and-Systems

About Aalborg University: According to the most recent US News and World Ranking, Aalborg University ranks 2nd in Europe and 16th in the world within Best Universities for Engineering. According to a 2018 MIT report, Aalborg University is considered to have the 4th best engineering program in the world. According to the recent Times Higher Education Impact ranking, Aalborg University ranks 9th in the World for UN SDG Impact.
6G-XCEL and Modelar DB
The 6G-XCEL project includes researchers from across the EU and the US and will develop a reference framework for AI in 6G that will pave the way toward global validation, adoption, and standardization of AI in 6G. Using the latest AI algorithms and data compression techniques as a starting point, 6G-XCEL will develop the Decentralized Multi-party, Multi-network AI(DMMAI) framework. Work on DMMAI will include the development of reference use cases, data and model repositories, curated training and evaluation data, AI-based methods and solutions for 6G, and technologies that enable use of DMMAI as a benchmarking platform for future AI solutions for 6G networks. More information about 6G-XCEL can be found at:https://www.6g-xcel.eu/.
To manage the extreme amounts of time series data in 6G-XCEL, the open source TSMS Modelar DB developed by Aalborg University will be used. Modelar DB provides lossless and lossy compression by fitting mathematical functions, e.g., constant or linear, to time series within a user-defined error bound(possibly zero). This compression is combined with a scalable query processing engine that can execute queries on the compressed representation to yield a unique combination of high compression, fast data ingestion, and scalable aggregate query processing. Modelar DB is implemented in Rust and uses Apache Data Fusion for query processing, Aparche Arrow for in-memory analytics, and Delta Lake with Apache Parquet for storage. More information about Modelar DB can be found at:https://github.com/skejserjensen/Modelar DB. The most recent version of Modelar DB can be found at:https://github.com/Modelar Data/Modelar DB-RS.
Research content:
In the 6G-XCEL project, Aalborg University will work on extending and optimizing Modelar DB for managing time series in 6G-XCEL's DMMAI framework. Thus, the purpose of this position is make Modelar DB efficiently support network data and low-powered network devices. As part of this, Modelar DB must be optimized for the domain specific requirements of 6G networks, e.g., hard real-time stream processing, and tighter integration with sensors and wireless access points. Modelar DB also lacks compressed representations specifically optimized for communication data, thus the development of such will also be part of the position.

Requirements:

• Ph D in computer science
• Excellent scientific background and publication record
• Demonstrated ability to work independently as well as in a team
• Excellent communication skills in English, oral as well as written
• Good low-level software development skills

Advanced experience in one or more of the following areas:

• Time series compression(lossy and/or lossless)
• Big data management and analytics
• Real-time stream processing
• Implementation of database management systems

Experience with the Rust programming language and the Apache Arrow ecosystem of libraries is an advantage.
Responsibilities:

• Participate in the 6G-XCEL research project
• Perform excellent scientific research
• Develop research prototypes and conduct experiments
• Integrate the proposed methods with or in Modelar DB
• Publish in leading international conferences and journals
• Participate in activities of the group and the department
• Documented experience with university teaching

Løn og ansættelsesvilkår

Employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities(the Appointment Order) and the Ministry of Finance's current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.

Ref. nummer

2024-224-06058

Ansøgningsfrist

01.10.2024