Funding
Self-funded
Project code
CMP10051025
Department
School of ComputingStart dates
October, February and April
Application deadline
Applications accepted all year round
Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.
The PhD will be based in the healthcare section of the 1024ºË¹¤³§ AI and Data Science Centre (formerly the Centre for Healthcare Modelling and Informatics), and will be supervised by Prof Jim Briggs, Prof David Prytherch and/or other members of the group.
The work on this project could involve:
- data science analysing anonymised clinical data from hospital patients
- contributing to a study furthering medical knowledge or hospital efficiency
The Centre for Healthcare Modelling and Informatics (CHMI) is a long-established health informatics research and innovation group. In collaboration with 1024ºË¹¤³§ Hospitals and others, our work in clinical outcome modelling has supported the development of the VitalPAC vital signs collection system (now known as CareFlow Vitals) and the National Early Warning Score (NEWS) recommended by the Royal College of Physicians and mandated by the NHS, among many other projects. More recently we have looked at how the risk to a patient may be predicted prior to surgery.
We are looking for high quality numerate graduates who wish to develop their data science skills on applications that may have rapid health service adoption. We work closely with our clinical partners to understand the ways in which their data is collected and how it can best be used to promote better outcomes for patients and better efficiency for the clinicians (e.g. doctors and nurses) involved and their organisations (e.g. hospitals).
We are particularly interested in work that monitors trends in a patient's condition over time, and identifying the appropriate point at which to intervene. Alternatively, we are broadening the scope of our work beyond its origins in general patient deterioration to other more specific medical areas, including surgery, intensive care and emergency medicine.
The successful candidate will join a team of academics, research staff and other PhD students who work closely with NHS clinicians and data scientists. We have excellent computing facilities and a friendly and supportive working environment
Fees and funding
Visit the research subject area page for fees and funding information for this project.
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK (UK and EU students only).
Bench fees
Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.
Entry requirements
You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a master’s degree in computer science or a related area. In exceptional cases, we may consider equivalent professional experience and/or Qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
High level of numeracy; confidence in dealing with data analysis. Previous health sector experience is not essential.
How to apply
We encourage you to contact Prof Jim Briggs (Jim.Briggs@port.ac.uk) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
When applying please quote project code: CMP10051025