As part of our ongoing investment in research, Middlesex University offers a number of funded studentships throughout the year.
Should any studentship become available, you can find details below.
We update these regularly, so if there isn't one at the moment, please check back shortly. You may also want to explore the new doctoral loan scheme.
Information and advice guides can be found at Student Finance England.
All our studentships are detailed below:
|Studentship||AI/machine learning for digital twin modelling in Industry 4.0|
|Sponsor||Middlesex University, Department of Design Engineering and Mathematics, Faulty of Science and Technology|
|Location||Hendon campus, London|
|Funding for||UK/EU Students|
|Application deadline||Open until the position filled|
|Start date||January 2020 (or as soon as possible after that)|
|Grant||Waived study fees + £12,000 per year for living expenses, during three years, to undertake a PhD at Middlesex University London|
|Period||Three years from the start date|
The rapid advancements in manufacturing technologies and industry transformation in 4th Industrial Revolution requires more sophisticated tools to enable high productivity, lower running costs, product quality improvement, minimized maintenance and shutdown. In Industry 4.0, fully automated smart industrial infrastructure relies on low latency feedback networks, high efficiency distributed control systems, fool-proof emergency and safety systems, energy efficient and self-sustaining processes and supportive digital technologies.
The existing industrial systems are highly complex and require several processes to operate simultaneously to achieve the desired objectives. To ensure efficient operations within industrial processes, human intelligence, intervention and feedback is widely used. To enable truly self-reliant and autonomous industries, the developments are on the way. One major hurdle in achieving fully autonomous industries is lack of software-based counterparts to support vigorous testing.
This project targets implementation of digital counterpart (a Digital Twin model) of Industry 4.0 to replicate its functionalities, data, communications, feedback, emergency and safety aspects. The proposed digital twin for industry 4.0 will not only offer a digitized replication of functionalities but will also enable development towards self-correcting smart process control facility. The digital twin will also facilitate debugging, testing and reforming processes. It is expected that the developments in the project will provide solutions for some of the most critical aspects of the present-day industries. The developments in this project will be cross-validated and vigorously tested in state of the art Siemens/Festo cyber factory facility installed at Middlesex University (UK), which acts as the physical twin in the project.
The key research question that will be addressed is how intelligently digital twin can predict the chain of events triggered as a consequence of certain variations in some processes, within the smart industries. The AI/machine learning tools should be employed to process the big data collected from the manufacturing systems and learn the pattern for the purpose of monitoring, control and predictive maintenance.
Applicants must have a minimum of a first or an upper second class honours degree or equivalent, and preferably a good master’s degree, in a relevant area. If your first language is not English, you should have a minimum IELTS score of 6.5 (with a minimum of 6.0 in each component) or TOEFL 575 (paper-based), 87 (with at least 21 in listening and writing, 22 in speaking and 23 in reading) (computer-based).
The candidate should be willing to travel to India.
To check your suitability, please send your CV and/or statement to Professor Huan Nguyen at H.Nguyen@mdx.ac.uk. If successful you will be directed to the online application portal.
|Studentship||Physical Literacy in London Primary Schools|
|Sponsor||Public Health Barnet|
|Qualification type||Masters of Science (by Research) – MSc by Research|
|Location||Hendon campus, London|
|Funding for||Full-time UK/EU students|
|Application deadline||Sunday 22 September 2019|
|Start date||September 2019|
|Grant||Waived study fees|
|Period||September 2019 to September 2020|
|Academic||Dr Lizi Smith (Principle investigator of physical literacy projects)|
It has been well documented that childhood obesity levels are constantly increasing. Physical activity has been highlighted as one of the main causes for obesity. However, in more recent years a concept that has been highlighted as more important than solely physical activity is physical literacy (PL). PL is described as ‘the motivation, confidence, physical competence and knowledge and understanding to engage in physical activity for life’.
However PL is a relatively new concept and this project looks to explore PL within a primary school setting in North London Schools. You will be required to work with teachers and children to carry out a mixed method analysis of PL and the understanding of PL.
The grant offered is to cover study fees for a full time MSc by Research student at Middlesex University. The candidate can be UK/EU based or International from outside the EU.
Please send an email to Dr Lizi Smith (L.Y.Smith@mdx.ac.uk) by Sunday 18 August 2019 (23:59pm UK time) with the subject “Application – physical literacy in primary schools” and attached the following documents:
Please note that the documents in the application must be genuine as the selected candidate will then have to submit a formal application the following week where study transcripts and other reassurances will be checked. Only upon receiving a formal offer letter from Middlesex University is the studentship applicant successful.
If you are pre-selected you will be called for interview where a final decision will be made. If you are selected for interview, you will be notified within a week of the deadline for applications. We are intending to carry out interviews in less than a month after the deadline for applications.
For more information on the scholarship, please email Dr Lizi Smith.