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Open Master's Applied Science Positions:



All of the following positions are currently open and have secured funding.

Note - All candidates are expected to already hold a bachelor's degree in Computer, Electrical, or Software Engineering or related field (i.e., Computer Science, Mathematics, or Physics).


  • NSERC funded positions:

    • Must follow NSERC Graduate student funding guidelines.
    • Must follow ECE Dept. funding guidelines.

  • Non-NESRC funded positions:

    • May or may not have similar guidelines (depends on funding source)
    • Can be used to ''top-up'' NSERC scholarships (for students holding them)
    • Must follow ECE Dept. funding guidelines.

Security Research Oriented Positions



Position S-A Position Filled. Peer-to-peer network detection (Non-NSERC Funded/Open/Immediately Available)

Peer-to-peer networks have become significant sources of network traffic.  Being able to accurately measure the traffic generated by these networks has become an important problem in the network management community.  This problem is exacerbated by the peer-to-peer community having spent (and continuing to spend) considerable effort in making their protocols and networks difficult to detect.  This is particularly true when peer-to-peer networks are actively used as conduits to disseminate illegal materials.  The goal of this project is to explore and begin to develop methodologies (primarily based on network traffic analysis approaches) to accurately detect these hard to detect peer-to-peer network, and particularly to develop techniques which are robust attempts to change the peer-to-peer network structure to subvert detection.

This research will be undertaken in collaboration with a large public sector organization.

This research will make direct use of the InSPiRe lab testbed for experimental work.

Ideal candidate: interest in network traffic analysis, interest in network security, interest in applied statistical analysis

Skills: some prior knowledge of computer networking, statistics, reasonable programming skills (for example C/C++, Perl, Matlab, etc.)

Position S-B Position Filled. Malware Classification (Non-NSERC Funded/Open/Immediately Available)

Malware is an on-going problem within IT systems security.  In particular, with large organizations it becomes important to be able to quickly classify novel malware such that "triage-like" decisions can be made in order to determine the appropriate level of response to take against these novel threats.  Statistical pattern recognition and classification approaches have shown some promise as a means of addressing this problem.  The goal of this research project is to more formally explore just how well these approach do indeed work and whether extensions exists which would improve there performance.

This research will be undertaken in collaboration with a large public sector organization and a local private company.

Ideal candidate: interest in malware analysis, interest in computer security, interest in pattern recognition and applied statistics

Skills: some prior of statistics, reasonable programming skills (for example C/C++, Perl, Matlab, etc.)

Distributed Software Systems Research Oriented Positions



Position D-A Analysis and Generation of Real-world Representative Distributed System Workloads (NSERC Funded/Open/Immediately Available)

Many real-world software systems operate as distributed systems, requiring many more than one computer on which to run.  The engineering of distributed software systems is much harder than the engineering of small-scale software applications.  In particular, it is well known that the performance of distributed software systems is highly dependent on the characteristics of the workloads that they must process.  The engineering of such systems, therefore, requires the ability to: (a) assess the statistical characteristics of a given real-world workload (or set of workloads), (b) to be able to re-create statistically similar workloads on demand, to support system testing efforts, and (c) to be able to explore ''what-if'' workload scenarios.  The goal of this project is to develop approaches which address each of these three interrelated areas.

This research will be undertaken in collaboration with a local private company.

This research will make direct use of the InSPiRe lab test bed for experimental work.

Ideal candidate: interest in distributed system performance/capacity analysis, interest in applied statistics, interest in real-time systems development

Skills: some prior of statistics, reasonable programming skills (for example C/C++, Perl, Matlab, etc.)

Position D-B Optimal Parameter Tuning of Distributed Systems (NSERC Funded/Open/Immediately Available)

Many real-world software systems operate as distributed systems, requiring many more than one computer on which to run.  The engineering of distributed software systems is much harder than the engineering of small-scale software applications.  In particular, getting good performance out of large-scale distributed systems can be a hard due to the large numbers of "tuneable" parameters which exist within such systems.  Obviously, "hand-tuning" such systems is infeasible as the scale of the system gets large.  The goal of this project is to develop techniques to automate this system tuning problem.

This research will be undertaken in collaboration with a local private company.

This research will make direct use of the InSPiRe lab test bed for experimental work.

Ideal candidate: interest in distributed system performance/capacity analysis, interest in applied statistics, interest in applied optimization (particularly genetic algorithms and similar approaches)

Skills: some prior of statistics, reasonable programming skills (for example C/C++, Perl, Matlab, etc.)

Position D-C Real-time Situational Awareness Visualizations for Enterprise-scale Distributed Systems (NSERC Funded/Open/Immediately Available)

 Many real-world software systems operate as distributed systems, requiring many more than one computer on which to run.  Visualizing what is happening in these systems is a hard problem, especially if the visualization is to be easily comprehended "at-a-glance".  The goal of this project is to develop "at-a-glance" visualization approaches for enterprise-scale distributed systems which ideally allow for the pre-emptive identification of performance breakpoints (i.e., points in the system where its resource capacity is becoming overwhelmed).

This research will be undertaken in collaboration with a local private company.

This research will make direct use of the InSPiRe lab test bed for experimental work. In particular, this position will make active use of the two 2x2 20" LCD displays (7.68 M pixels per display) which are available for visualization work.

It should be noted that this research has a close relation to security oriented research in the "at-a-glance" visualizations for tactical situational awareness.

Ideal candidate: interest in real-time systems, interest in human factors analysis, interest in visualization approaches for large complex domains

Skills: interest in real-time systems, interest in human factors analysis, interest in visualization approaches for large complex domains


2003 - 2012 Information Security and Privacy Research (InSPiRe) Laboratory, University of Victoria

 
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