The successful candidate will join the “Big Data” group led by Martin Theobald on the Belval Campus of the University of Luxembourg. You will contribute to a research project on large-scale, real-time analysis of streaming data within a newly developed Distributed Stream-Processing System (DSPS). The PhD position is settled within the newly established DRIVEN (“Data-Driven Computational Modelling and Applications”, see https://driven.uni.lu) doctoral training unit at the University of Luxembourg which overall consists of 19 interdisciplinary PhD projects. We also intend to closely collaborate with the HPC group (see http://hpc.uni.lu/) which currently manages 4 data centres with an overall capacity of more than 11K cores and 10PB of storage.
Your activities include:
- Conducting basic research and contributing to international publications in the area of Big Data Analytics
- Developing software prototypes and experimentally compare your developed approaches against the various Big Data platforms (such as Hadoop, Spark, Flink, etc.)
- Assisting in the organization of Bachelor/Master projects and courses
For further information, please contact firstname.lastname@example.org
- M.Sc. degree in Computer Science or closely related field
- Strong mathematical and algorithmic background
- Excellent, proven programming skills in C/C++ are required
- Additional knowledge of Java, Scala, Python is a plus
- Background in distributed architectures (MPI, SLURM, Hadoop, Spark) is a plus
- Good communication skills, commitment, team working, and a critical mind
The University is an equal-opportunity employer. Fluent written and verbal communication skills in English are mandatory. The University of Luxembourg is a young, multilingual and international research university. The communication in the research groups is in English, while teaching is conducted in English, French and German. You will work in an exciting international environment and will have the opportunity to participate in a state-of-the-art research topic at the intersection of Big Data Analytics, Data Mining and Machine Learning.
Applications, in English, should include:
- Curriculum vitae, including your current contact address, transcript of certificates and grades (with a detailed list of university courses taken) and your previous publications (if any)
- Cover letter and research statement indicating your topics-of-interest and motivation to apply for the position (max 1 page)
- Contact information for 2 referees at your current and/or previous affiliations
Early submission is encouraged; applications will be processed upon arrival. The position is intended to be filled in early 2020.