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.
Location
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.
Qualifications
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.
Contact
Please contact:
with your CV, and Bachelor's and Master's degree transcripts, email to bigdata@unb.ca
Applications are being considered immediately.
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