PhD Scholarship (Canada) in Scalable Big Data Systems on Modern Hardware

Research project

Data systems are going through a major transition due to the challenges of Big Data processing. The volume and velocity of data generated from a variety of sources are far outpacing the available storage and processing capacity – the term Big Data is used to signify this. Data science enables one to bring structure to large quantities of data and make analysis possible. However, existing data systems are not able the meet the computational challenges of data-intensive applications. The goal of the research will be to devise new approaches to data processing that can support analysis on data at massive scales. The advent of multi-core processors, along with the ever growing main memory, has fundamentally changed how Big Data is processed. Therefore, the project will particularly investigate scalable runtime for data processing infrastructure on modern hardware, by exploiting the growing memory, multi-core architecture and GP-GPUs. This is a fully funded (i.e. full scholarship) PhD position. 


The research will be conducted at the Big Data Systems and Analytics Lab of the Faculty of Computer Science, University of New Brunswick, Fredericton. The University of New Brunswick, Fredericton is one of the top comprehensive universities of Canada. The Faculty of Computer Science is the first faculty of computer science in Canada and a leader in Atlantic Canada since 1968 with the oldest and most successful COOP program in Atlantic Canada.


You have a solid background in Computer Science, Computer Engineering or in a related discipline. It is expected that you have a Master's level degree from a reputed university with excellent grades. An exception can be made for truly outstanding candidates with a Bachelor's degree, but without a Master's degree. Also, you should have strong programming and software implementation skills. Programming expertise, particularly in C/C++ and Java is necessary is desired.

The project will explore high performance SQL query processing approaches using cutting-edge query compilation techniques. Therefore, good knowledge in database internals and compiler design is helpful. Familiarity with distributed Big Data frameworks like Hadoop and Spark is beneficial. Any previous experience or internship in Data Science, machine learning or data mining is appreciated. Previous research experience or work experience in the software industry is a strong asset. 

Qualities such as being able to take initiatives and work independently, a genuine sense of curiosity in the subject matter, as well as debugging skills, and excellent analytical skills are highly valued.


Please contact: with your CV, and Bachelor's and Master's degree transcripts, email to

Applications are being considered immediately.