Mental health Data Science: Fully Funded PhD Studentship in Machine learning modelling of self-harming and suicidal behaviours based on country- and person-level indicators (RS906)

Funding providers: HCRW 

Subject areas: Machine Learning; Suicide; Self-harm; Mental Health 

Project start date: 01/01/2026 ** (Please see the note below regarding potential later start dates.)

Supervisors: 

• First supervisor: Prof Ann John – Professor of Public Health and Psychiatry 
• Second supervisor: Dr Marcos Del Pozo Banos – Senior Lecturer on Mental Health Data Science  

Aligned programme of study: Population and Health Data Science PhD 

Mode of study: Full-time 

Project description:
Proposed topic: “Creating a National Digital Twin for self-harming and suicidal behaviours”  

Self-harm and suicide are increasingly recognised public health priorities globally, leading to greater political commitment and a surge in scientific inquiry. However, the wide range and vast number of influencing factors makes understanding, preventing, and treating these behaviours highly challenging. This is further hindered by a lack of diverse big data resources and matched, powerful analytical tools. As a result, progress in the field has been characteristically slow over the last 50 years.  

The National Centre for Suicide Prevention and Self-harm Research (NCSR) is tackling these barriers by putting together a world-leading data resource on suicide and self-harm, and powerful machine learning methodologies compatible with epidemiological principles to produce high-quality evidence and tools.  

In this inter-disciplinary PhD project, you will collaborate with other researchers from the NCSR in the above mission. You will:  

1. Help collate data resources relevant to suicide and self-harm. 
2. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and others) compatible with epidemiology.  
3. Produce a digital twin for national suicide and self-harm rates.  

You will expand your data wrangling, analytical and programming skills on python and develop expertise in the fields of machine learning, epidemiology, big data analysis, and suicide and self-harm. 

Your work will expand the frontier of machine learning applications in epidemiology and improve our understanding of suicide and self-harm. It will also directly inform the development of a support tool to design targeted interventions, efficient policies and national strategies. Above all, your work will be in a privileged position to have a real-world impact, helping improve the life of those most vulnerable. 

Scholarship open to UK fee eligible applicants only.  

PhD: Applicants for PhD must hold an undergraduate degree at 2.1 level and a master’s degree. Alternatively, applicants with a UK first class honours degree (or non-UK equivalent as defined by Swansea University) not holding a master’s degree, will be considered on an individual basis. 

English Language 
IELTS 6.5 Overall (with no individual component below 6.5) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found here. 

Note for international and European applicants: details of how your qualification compares to the published academic entry requirements can be found on our Country Specific Entry Requirements page. 

This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £20,780 for 2024/25).

To apply, please complete the entire application form:

In order to be considered for this scholarship award the following steps are also required. 

1) In section ‘Programme Related Information’ please input the relevant RS Code for the scholarship award i.e. RS906 

2) In section ‘Research’ you will see ‘Proposed project title/studentship title’* (Mandatory) 

• In ‘Proposed project title/studentship title’ please input:  
  • the RS Code, RS906 and 
  • the scholarship title.   
• Please leave Proposed Supervisor field blank 
• Please leave Research Project (if applicable) blank 
• In ‘Do you have a proposal to upload?*’(Mandatory) Please select Yes 
• Then upload copy of advert (you can save the advert by clicking print, and then print to pdf) 

3) In section ‘Funding information’ please choose the option ‘Scholarship Funding’ only. Please ensure no other options are selected.  

*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award. 

If you’ve previously applied for this programme, the system will display an “Application Submitted” warning and block a new submission. In this case:  

1. Apply for the same course with the next available start date (e.g., select January if October is unavailable).  
2. Email pgrscholarships@swansea.ac.uk with your student number and the relevant scholarship RS code, requesting the start date be amended to match the advert.  
3. Admissions staff will then update your application accordingly.  

One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards. 

NOTE: Applicants for PhD/EngD/ProfD/EdD - to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University you are required to complete an Equality, Diversity and Inclusion (EDI) Monitoring Form in addition to your programme application form.    

Please note that completion of the EDI Monitoring Form is mandatory; your application may not progress if this information is not submitted. 

As part of your online application, you MUST upload the following documents (please do not send these via email): 

• CV 
• Degree certificates and transcripts (if you are currently studying for a degree, screenshots of your grades to date are sufficient) 
• A cover letter including a ‘Supplementary Personal Statement’ to explain why the position particularly matches your skills and experience and how you choose to develop the project. 
• One reference (academic or previous employer) on headed paper or using the Swansea University reference form. Please note that we are not able to accept references received citing private email accounts, e.g. Hotmail. Referees should cite their employment email address for verification of reference. 
• Evidence of meeting English Language requirement (if applicable). 
• Copy of UK resident visa (if applicable) 
• Confirmation of EDI form submission 

Informal enquiries are welcome; please contact Ann John on A.John@Swansea.ac.uk and Dr Marcos Del Pozo Banos on M.Delpozobanos@Swansea.ac.uk  

*External Partner Application Data Sharing – Please note that as part of the scholarship application selection process, application data sharing may occur with external partners outside of the University, when joint/co- funding of a scholarship project is applicable. 

** In exceptional circumstances, and subject to the discretion of the University and/or the relevant funding body, a deferral of offer may be granted to the next available enrolment period. Such deferral will typically not exceed a duration of three calendar months from the originally stipulated commencement date. Please note that only one deferral may be considered, and any such deferral is not guaranteed.