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PhD Studentship - Remote Follow-up and Assessment of Wounds

University of Hull

Qualification Type: PhD
Location: Kingston upon Hull
Funding for: UK Students
Funding amount: £18,622 - please see advert
Hours: Full Time
Placed On: 20th November 2023
Closes: 15th February 2024

About this Project:

Timely and accurate diagnosis of wound infections is pivotal in preventing their escalation into more serious health issues.

This interdisciplinary project will involve working collaboratively with the University’s Centre of Excellence for Data Science, Artificial Intelligence and Modelling (DAIM), and the Academic Vascular Surgical Unit (AVSU) to develop a valid, reliable, sensitive, specific and acceptable pathway to enable healthcare providers to remotely assess and manage patients with wounds, whilst evaluating the reduction in environmental impact achieved through the implementation of this approach.

This pathway will be instrumental in enabling healthcare providers to remotely and accurately identify patients at risk, ensuring they receive the prompt attention and follow-up appointments they require.

By undertaking this PhD, the candidate will play an instrumental role in shaping the future of wound care and healthcare sustainability.

For informal enquires please contact:

Vascular Research Manager - Judith Long: Judith.long3@nhs.net

About the Research Cluster:

The PhD cluster is embedded in a multidisciplinary and highly collaborative network across the University of Hull, Hull University Teaching Hospitals NHS Trust and Industry. The successful candidates will have access to the new clinical and office areas within the Allam building (Hull University Teaching Hospitals NHS Trust), facilitating data collection and valuable hands-on clinical exposure. Additionally, they will enjoy state-of-the-art research facilities at the newly established Melton location (S&N Wound Care Facility) with access to advanced laboratories equipment and the recently inaugurated UoH campus DAIM centre which boasts state-of-the-art machine learning software and computational resources.

Supervisors:

  • Professor Adil Khan, Professor of Machine Learning (ML) and Artificial Intelligence (AI)
  • Mr George Smith Senior Lecturer
  • Dr Ross Lathan, Academic Clinical Fellow

Funding:

The successful applicant will receive a fee waiver and a maintenance grant / stipend for three years (full-time) or six years (part-time), which covers the research period of the PhD. The fee waiver for 23/24 is £4,712 (Home fee) and the maintenance grant is £18,622 per annum. If you need to move into a fourth year (full time) or seventh year (part-time) to complete your thesis, please note that you will not receive a tuition fee waiver or maintenance grant during this period and you will be required to pay a continuation fee.

Entry Requirements:

Essential - Applicants should have a minimum 2:1 degree in a related subject.

Desirable - A taught MSc or Masters by Research in a relevant subject.

For more details on our entry requirements please visit the postgraduate admissions webpage.

This scholarship is available for full-time and part-time study.

International applicants:

This opportunity comes with a Home fee waiver only, which will not cover the full International fee. You will therefore need to pay the difference between the Home fee and the International fee and will need to provide evidence that you have sufficient funds to cover this.

Apply:

Please supply a personal statement when applying for this scholarship position. Find out more about writing a personal statement.

Apply here for the Scholarship

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