Mental health Data Science: Fully Funded PhD Studentship in Machine learning modelling of self-[...]

Swansea University; United Kingdom; On-site; GBP 21,000; Full time

Job summary

A prominent UK university is offering a PhD position focused on creating a digital twin for understanding self-harming and suicidal behaviors. This role requires strong skills in data wrangling, machine learning, and programming, aimed at improving interventions and policies for vulnerable communities. The scholarship covers full tuition fees and an annual stipend at UKRI rate of £20,780.

Benefits

Full cost of tuition fees

Annual stipend at UKRI rate

Qualifications

• PhD applicants must have a relevant undergraduate degree and a master's degree.
• UK first class honours degree holders without a master's may be considered.

Responsibilities

• Collate data resources relevant to suicide and self-harm.
• Develop new machine learning methodologies compatible with epidemiology.
• Produce a digital twin for national suicide and self-harm rates.

Skills

Data wrangling

Analytical skills

Programming in Python

Machine learning methodologies

Education

Undergraduate degree at 2.1 level

Master's degree

First class honours degree

Job description

Organisation/Company Swansea University Department Central Research Field Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 27 Nov 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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

Self-harm and suicide areincreasingly recognized public health priorities globally, leading to greater political commitment and a surge in scientific inquiry. However, the wide range and vast number of influencing factorsmakesunderstanding, 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 methodologiescompatible withepidemiological principlesto producehigh-qualityevidence and tools.

In thisinter-disciplinaryPhD project,you willcollaborate with other researchers from the NCSR in the above mission. You will:

• Help collate data resourcesrelevant to suicide and self-harm.
• Developnewmachine learning methodologies(fromartificial neural networks,decision trees,evolutionaryalgorithmsand others) compatible with epidemiology.
• Produce a digital twin for national suicideand self-harmrates.

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

Your work willexpandthe frontier ofmachine learning applications in epidemiology and improve our understanding of suicide andself-harm. It will alsodirectlyinform the development of a support tooltodesigntargeted interventions,efficientpoliciesand national strategies.Above all, yourwork will be in a privileged position to have a real-world impact, helping improve the life of those most vulnerable.

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.

Specific Requirements

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 (ornon-UKequivalent as defined by Swansea University) not holding a master’s degree, will be considered on an individual basis.

Additional Information

This scholarship covers thefull cost of tuition feesand an annual stipend atUKRI rate (currently £20,780for 2024/25).

Eligibility criteria

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 (ornon-UKequivalent as defined by Swansea University) not holding a master’s degree, will be considered on an individual basis.

Selection process

Please see our website for further information