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Hybrid modelling and implementation-based accurate and scalable digital twining of buildings


   Centre for Digital Innovation

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  Dr Joshua Balota  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

We are pleased to invite UK, EU and international applications for a fully-funded PhD studentship in Hybrid modelling and implementation-based accurate and scalable digital twining of buildings from Teesside University’s Centre for Digital Innovation.

Project description

We are experiencing a cabalistic transformation in manufacturing products because of the digitisation of the process of manufacturing products in the industries and factories. The key technologies in this transformation are, Cyber Physical Systems, Internet of Things (IoT) and Information Systems. The transformation is so significant and inevitable that it is being considered as the 4th industrial revolution called Industry 4.0.

A digital twin (DT) is a virtual and IoT-connected replica of a process or product. Through IoT-gathered real-time data, a DT of a process or product can understand the current state, simulate or predict the future state, and optimise performances. It can control systems anticipating problems, in silico development, and real-time asset management of a product or a process, including buildings, cities, and offer smarter and energy efficient management of the product or process.

Modelling of a physical process or product and the connection between the physical process or product and the corresponding virtual model are two main requirements for a DT. The connection is established by generating real-time data using sensors and sharing through an IoT. Modelling in DT can be done in one of the three ways: physics-based, data-driven, and hybrid. Hybrid modelling is the preferred approach for the most existing DT solutions as it removes the shortfalls of a pure physics-based or pure data-driven modelling approach. Hybridisation techniques can be a combination of different levels of contribution from the pure modelling approaches.

This project aims to design and develop an accurate and scalable DT solution for buildings using a hybrid modelling and implementation approach.

The supervisor is Dr Josiah Balota from the School of Computing, Engineering & Digital Technologies.

Entry requirements

You should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A master’s level qualification in a relevant discipline is desirable, but not essential, as well as a demonstrable understanding of the research area.

International applicants should have a standard of English at IELTS 6.5 minimum and will be subject to the standard entry criteria relating to ATAS clearance and, when relevant, UK visa requirements and procedures.

How to apply

Application is online.

Key dates

  • Closing date for applications is 5.00pm, 1 February 2023.
  • Shortlisting and online interviews are expected to be held mid-March 2023.
  • Successful applicants will be expected to start May or October 2023.

Funding Notes

The Fully Funded PhD Studentship covers tuition fees for the period of a full-time PhD Registration of up to four years and provide an annual tax-free stipend of £17,668 for three years, subject to satisfactory progress.
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