Enhancing System Architecture
Location: Joondalup, WA
Duration: 3 months
Proposed start date: May 2019
Cinglevue International is a medium-sized systems integrator providing specialist services and innovative solutions to organisations within the Early Years Learning to Higher Education space. Cinglevue are currently developing an enterprise learning and instructional support platform called Virtuoso; an end-to-end, data-driven solution emphasising the recognition of individual differences in support of targeted learning pathways and experiences for each student. Virtuoso utilises sophisticated data-driven capabilities to provide students, teachers, guardians, and administrators with the necessary tools and information to make informed decisions in order to further educational outcomes.
Cinglevue are seeking a PhD student with expertise in computer science, systems architecture, and machine learning to investigate and subsequently enhance Virtuoso’s capacity to support event-driven, real-time data streaming applications. The student will work closely with our Engineering team to explore their existing implementation and contribute towards the development of a successful architecture through the building of prototypes and Proofs of Concept (POCs) which interface with the Virtuoso data lake. From this, a generaliseable, extensible, and flexible architectural solution will be derived which can accommodate a wide range of educational use cases.
Research to be Conducted
The purpose of the internship will be to investigate and evolve a system architecture for the Virtuoso platform that supports a broad range of event-driven and real time data streaming use cases through collaborative engagement with Cinglevue’s Engineering team as well as via the use of prototyping within an experimental paradigm. To this end, the internship will need to address the following research questions:
- To what extent does Virtuoso’s current architecture support event-driven and real time data streaming applications?
- How can Virtuoso’s architecture be enhanced to improve support for event-driven and real time data streaming applications?
- How can prototypes/ POCs be used to support the development and validation of an enhanced architecture within an experimental paradigm?
- How can this be done so in a way that readily lends itself to subsequent machine learning applications as well as future enhancements to the platform?
- What guidelines and recommendations can be developed in light of the above to support the ready development and implementation of use cases that incorporate event and real-time data streaming?
We are looking for a PhD student with the following:
- Computer Science /Machine Learning Systems Architecture
- Demonstrated ability to assess and solve complex problems and systems
With reference to the research questions detailed in Section 3, the following project deliverables are expected to be produced by the Intern:
- A detailed report evaluating the current Virtuoso system architecture in terms of its capacity for supporting event and real-time data streaming applications. Note that this evaluation should be undertaken from an enterprise architecture perspective and should take into account continued development and expansion of the Virtuoso platform feature set.
- Development of numerous prototypes/POCs for experimenting with a range of potential event and real-time data streaming use cases which interface with the Virtuoso data lake (as well as the Virtuoso Business Process Modelling engine where appropriate). Events could incorporate user interaction with the system at a macroscopic level (accessing particular modules within the system, triggering specific functionality, etc.), as well as more granular interactions within specific learning activities (student interacting with particular interface elements, making decisions, submitting answers, etc.). Similarly, real-time streaming interactions would be expected to encompass scenarios were immediacy is paramount and access to current data insights are needed to inform decision-making and approaches to practice (e.g. a teacher wants to see student responses during an in-class assessment as they are captured by the system such that the following parts of the lesson and subsequent interaction with students can be modified accordingly).
- An enhanced architectural model for the Virtuoso platform based on outcomes and findings from phases (1) and (2). Developed in close collaboration with the Engineering team, the enhanced architectural model will need to take into account existing requirements and considerations concerning the Virtuoso platform as a whole and be enterprise capable. This will also involve developing a plan for transforming the existing architecture in an appropriate manner to accommodate the enhancements that have been identified.
- A final report detailing findings, considerations, guidelines, and best practices based on the Intern’s experience throughout the project which can be used to inform future developments as well as use cases pertaining to event and real-time data streaming applications within Virtuoso.
The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.
It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
08 May 2019
APR – 0858