Supervisors

Lead supervisor Dr Maedeh Mansoubi, University of Exeter, Department of Medicine

Co-Supervisor Professor Helen Dawes, University of Exeter, Department of Medicine

The GW4 BioMed2 MRC DTP is offering up to 21 funded studentships across a range of biomedical disciplines, with a start date of October 2025.

These four-year studentships provide funding for fees and stipend at the rate set by the UK Research Councils, as well as other research training and support costs, and are available to UK and International students.

About the GW4 BioMed2 Doctoral Training Partnership

The partnership brings together the Universities of Bath, Bristol, Cardiff (lead) and Exeter to develop the next generation of biomedical researchers. Students will have access to the combined research strengths, training expertise and resources of the four research-intensive universities, with opportunities to participate in interdisciplinary and 'team science'. The DTP already has over 90 studentships over 6 cohorts in its first phase, along with 58 students over 3 cohorts in its second phase.

The 120 projects available for application, are aligned to the following themes;

• Infection, Immunity, Antimicrobial Resistance and Repair

• Neuroscience and Mental Health

• Population Health Sciences

 

Applications open on 10th September 2024 and close at 5.00pm on 4th November 2024.

Studentships will be 4 years full time.  Part time study is also available.

Project Information

Research Theme:

Neuroscience & Mental Health

Summary:

Fatigue is a major issue for individuals with neurological conditions, often leading to lower quality of life. This project aims to empower these individuals through an AI-powered fatigue management tool using data fusion from wearable technologies that track physiological data, such as heart rate, sleep patterns, and physical activity, combined with an app to log symptoms. A machine learning algorithm will be developed to predict fatigue patterns, allowing users to plan activities and rest proactively. This tool will help organise tasks and energy management, send personalised reminders, and support better fatigue management while assisting healthcare professionals in making informed decisions.

Project Description:

Fatigue is a significant issue for individuals with neurological conditions, often resulting in lower quality of life and social isolation. Currently, no system utilises data fusion to predict fatigue based on individual data, hindering effective symptom management. To address this, the project aims to empower these individuals by leveraging wearable technologies to monitor physiological data (such as heart rate, sleep patterns, and physical activity) and AI-driven apps to log symptoms and track fatigue levels. This approach provides tailored advice based on specific conditions and daily routines, fostering a sense of control and independence in managing health and monitoring fatigue in real time. The collected data will be used to develop AI algorithms capable of predicting periods of high fatigue, enabling proactive activity and rest planning. By analysing patterns, identifying triggers, and correlating factors that exacerbate fatigue, these algorithms will assist both individuals and healthcare providers in managing fatigue more effectively. The predictive model will be instrumental in foreseeing  highfatigue periods, allowing for better activity planning and rest. As part of the PhD program, an AI-powered tool will be co-developed to assist individuals with neurological conditions in organising and
prioritising tasks and energy management. This tool will focus on essential activities, predict fatigue risk, and send personalised reminders to take breaks, perform relaxation exercises, or engage in low-intensity activities based on personalised data. This proactive approach promotes better fatigue management throughout the day.

Additionally, this tool will aid healthcare professionals by analysing patient data to identify trends, suggest interventions, and personalise treatment plans, enhancing fatigue management and consultation effectiveness. Integrating AI-driven insights into everyday health management will improve the quality of life for individuals with
neurological conditions by providing real-time support and personalised care strategies.

Key Research Question

The project's primary research question is: How can wearable technologies and AI-driven applications be integrated to predict and manage fatigue in individuals with neurological conditions, thereby enhancing their quality of life and independence?

Specific Objectives

The studentship will focus on the following specific objectives:

1. Data Collection and Integration:
• Implement wearable technologies to continuously monitor physiological data such as heart rate, sleep patterns, and physical activity.
• Develop methods to integrate this data into a central system for analysis seamlessly.
2. AI Algorithm Development:
• Create AI algorithms to analyse the collected data to identify patterns and predict periods of high fatigue.
• Develop predictive models to understand triggers and correlating factors that exacerbate fatigue.
3. Symptom Tracking and Management:
• Design AI-driven applications that help individuals log their symptoms and track real-time fatigue levels.
• Provide tailored advice and personalised recommendations based on the individual’s specific conditions and daily routines.
4. Proactive Fatigue Management:
• Develop an AI-powered tool to assist in organising and prioritising tasks, focusing on essential activities.
• Implement personalised reminders for breaks, relaxation exercises, and low-intensity activities to manage fatigue proactively throughout the day.
5. User Experience and Feedback:
• Conduct user testing to gather feedback on the effectiveness and usability of the AI-driven applications and tools.
• Iterate and refine the tools based on user feedback to ensure they effectively meet the needs of individuals with neurological conditions.

By achieving these objectives, the project aims to provide a comprehensive, AI-powered solution that empowers individuals with neurological conditions to manage their fatigue more effectively, enhancing their quality of life and independence. Integrating predictive modelling and personalised health management tools will help healthcare professionals deliver more informed and tailored care.

Funding

This studentship is funded through GW4BioMed2 MRC Doctoral Training Partnership. It consists of UK tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£19,237 p.a. for 2024/25, updated each year).

Additional research training and support funding of up to £5,000 per annum is also available.

Eligibility

Residency:

The GW4 BioMed2 MRC DTP studentships are available to UK and International applicants. Following Brexit, the UKRI now classifies EU students as international unless they have rights under the EU Settlement Scheme. The GW4 partners have agreed to cover the difference in costs between home and international tuition fees. This means that international candidates will not be expected to cover this cost and will be fully funded but need to be aware that they will be required to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.  All studentships will be competitively awarded and there is a limit to the number of International students that we can accept into our programme (up to 30% cap across our partners per annum).

Academic criteria:

Applicants for a studentship must have obtained, or be about to obtain, a first or upper second-class UK honours degree, or the equivalent qualification gained outside the UK, in an appropriate area of medical sciences, computing, mathematics or the physical sciences.  Applicants with a lower second class will only be considered if they also have a Master’s degree. Please check the entry requirements of the home institution for each project of interest before completing an application. Academic qualifications are considered alongside significant relevant non-academic experience.

English requirements:

If English is not your first language you will need to meet the English language requirements of the university that will host your PhD by the start of the programme. Please refer to the details in the following web page for further information https://www.exeter.ac.uk/study/englishlanguagerequirements/

Data Protection

If you are applying for a place on a collaborative programme of doctoral training provided by Cardiff University and other universities, research organisations and/or partners please be aware that your personal data will be used and disclosed for the purposes set out below.

Your personal data will always be processed in accordance with the General Data Protection Regulations of 2018. Cardiff University (“University”) will remain a data controller for the personal data it holds, and other universities, research organisations and/or partners (“HEIs”) may also become data controllers for the relevant personal data they receive as a result of their participation in the collaborative programme of doctoral training (“Programme”).

Further Information

For an overview of the MRC GW4 BioMed programme please see the website www.gw4biomed.ac.uk

Entry requirements

Academic Requirements

Applicants for a studentship must have obtained, or be about to obtain, a first or upper second-class UK honours degree, or the equivalent qualification gained outside the UK, in an appropriate area of medical sciences, computing, mathematics or the physical sciences. Applicants with a lower second class will only be considered if they also have a Master’s degree. Please check the entry requirements of the home institution for each project of interest before completing an application. Academic qualifications are considered alongside significant relevant non-academic experience.

English Language Requirements

If English is not your first language you will need to meet the English language requirements of the university that will host your PhD by the start of the programme. Please refer to the relevant university website for further information.  This will be at least 6.5 in IELTS or an acceptable equivalent.  Please refer to the English Language requirements web page for further information.

How to apply

A list of all the projects and how to apply is available on the DTP’s website at gw4biomed.ac.uk.  You may apply for up to 2 projects and submit one application per candidate only.

Please complete an application to the GW4 BioMed2 MRC DTP for an ‘offer of funding’.  If successful, you will also need to make an application for an 'offer to study' to your chosen institution.

Please complete the online application form linked from our website by 5.00pm on Monday, 4th November 2024.  If you are shortlisted for interview, you will be notified from Friday, 20th December 2024.  Interviews will be held virtually on 23rd and 24th January 2025.

Further Information

For informal enquiries, please contact GW4BioMed@cardiff.ac.uk

For project related queries, please contact the respective supervisors listed on the project descriptions on our website.

Summary