Project objectives: 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. 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 science applications. Through this project the researcher will devise new approaches to data processing that can support analysis on data at massive scales. The goal of the project is to design and develop novel compiler and runtime techniques to support scalable processing of Big Data. The project will also investigate parallel runtime for data processing infrastructure on modern hardware.
Location: 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.
Description: This research project will develop scalable big data systems using compiler and runtime techniques. The researcher will explore high performance SQL query processing approaches using cutting-edge query compilation techniques. Therefore, good knowledge in database internals and compiler design is desired. Familiarity with distributed Big Data frameworks like Hadoop and Spark is beneficial. This is a fully funded (i.e. full scholarship) PhD position.
Qualifications: A solid background in Computer Science (or Computer Engineering), including a thesis-based research Master’s level degree from a reputed university with excellent grades, is required. Strong programming skills in C/C++ and Java are expected. Solid understanding of database system internals, compiler design, parallel programming, and Linux systems programming are advantageous. Familiarity with relational databases like PostgreSQL, MySQL, and data science/machine learning libraries is appreciated.
Contact: Please contact with your CV, and Bachelor’s and Master’s degree transcripts; Email to [email protected]