Research 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.
The goal of the research will be to devise new approaches to data processing
that can support analysis on data at massive scales.
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.
PhD positions
There are two PhD positions available and they are fully
funded. For both positions a solid background
in Computer Science (or Computer Engineering), including a Master's level
degree from a reputed university with excellent grades, is required. Also, strong programming and software
implementation skills are desired. 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. Previous research experience or
work experience in the software industry is an asset. Further details of each position and
requirements are as follows.
Position
1: High performance query
processing system
This PhD research will develop high performance SQL
processing approaches using cutting-edge query compilation techniques, while taking
advantage of modern multicore hardware, as well as distributed Big Data
frameworks like Hadoop and Spark. Strong
programming background in C/C++ and Java is necessary, and knowledge of Python
is expected. Solid understanding of and experience with database system
internals, compiler design and Linux systems programming are advantageous.
Position
2: Scalable parallel runtime for Data
Science
This PhD research will focus on developing high
performance parallel runtime infrastructure for Data Science applications on
modern hardware. Strong programming skills
in Python and C/C++ are important. Any prior experience in parallel
programming, Linux systems programming and language runtimes can be asset.
Familiarity with Python Data Science echo-system, including Numpy and Pandas, machine
learning or data mining libraries is appreciated.
Contact
Please contact:
with your CV, and Bachelor's and Master's degree transcripts, email to bigdata@unb.ca
.
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