Title: SH17: Digital twins for intelligent asset monitoring and advanced simulation
Funding: Full time Home/EU and overseas fee waiver (further fee details) and a stipend of £15,009 p.a.
Application deadline: 9 August 2019
Start date: October 2019
Duration: 3 years (full time)
Location: Colchester Campus
This studentship is now closed. Please view our other opportunities.
A digital twin is a digital representation of a real-world entity or system that mirrors a unique physical object. Data from multiple digital twins can be aggregated for a composite view across a number of real world. Digital twins could enhance data insights and improve decision making by their ability of collecting and visualising real-time data, enabling smart analytics and customised rules to effectively achieve business objectives.
Digital twins could consolidate massive amounts of information on individual assets and groups of assets, providing monitoring and control of those assets. For example, operations managers could use them for real-time monitoring, for advances simulation, or for cost-benefit analysis of risks; developing new business models.
Furthermore, twins could be able to communicate with one another to create digital models of multiple linked digital twins. Digital twins are built on the concept that virtual asset models coexist and are connected to real assets; however, this concept isn't limited to assets (or things). It could be possible to include digital analogies of real-world elements based on metadata structures, connecting these digital representations/models to their real-world counterparts.
Therefore, digital twins of assets could be linked to other digital entities for people (digital personas), processes (law enforcement) and spaces (digital cities). Understanding the links across these digital entities, isolating elements where needed and tracking interactions will be vital to support a secure digital environment. Using AI-based models could create mixed reality environments for advanced simulation, operations and analysis.
The PhD project aims to investigate the applications of digital twins to support BT business operating models, focusing on advanced simulation (e.g. smart building/assets simulation), operation and data analysis.
The studentship will be part of the Intelligent Embedded Systems and Environments (IESE) research group in the School of Computer Science and Electronic Engineering (CSEE) at the University of Essex. However the successful candidate will be expected to split their time between the University of Essex campus and also work at BT’s research and development site at Adastral Park, Ipswich.
The award consists of a full Home/EU or overseas fee waiver (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 in 2019-20), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
At a minimum, the successful applicant will have a good honours BSc degree (1st class or high 2:1, or equivalent) in computer science or related subjects. An MSc with Merit or Distinction is desirable (but not essential for students with a first class degree). Strong analytical and mathematical skills are required, as well as good programming skills.
Understanding and/or experience in/of:
You can apply for this postgraduate research opportunity online.
Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.
The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.
Instruction to applicants
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the supervisor, Dr Michael Gardner (email@example.com)