Phenotyping Anorexia of Ageing Risk: Integrating Population-Scale Data Science with Mechanistic Characterisation of Appetite Control

About the Project

Are you interested in applying artificial intelligence and machine learning to tackle one of the most important challenges in healthy ageing?

Applications are invited for an interdisciplinary PhD studentship investigating anorexia of ageing: the age-related loss of appetite contributing to undernutrition, frailty, and loss of independence in later life.

This programme of research will use advanced artificial intelligence and machine learning approaches to analyse large-scale population data from UK Biobank to identify distinct risk phenotypes for anorexia of ageing. These insights will be integrated with laboratory-based research examining appetite regulation and metabolic responses in older adults, providing a unique opportunity to link population-scale epidemiology and data science with mechanistic physiology.

The successful candidate will receive exceptional interdisciplinary training across artificial intelligence, epidemiology, physiology, and biochemistry. You will gain experience applying machine learning methods to complex health datasets, alongside hands-on training in human appetite research and biochemical analyses.

The student will become an active member of two internationally recognised research environments: the Human Nutrition and Exercise Research Centre (HNERC) and the Interdisciplinary Computing and Complex BioSystems (ICOS) research group. This vibrant and collaborative environment provides excellent opportunities for networking, skill development, and career progression.

Upon successful completion of this programme of research, you will be well positioned to pursue research careers spanning data science, physiology, nutrition, and biomedical science.

The successful candidate will:

• Receive exceptional training across diverse interdisciplinary research skills.
• Adopt transformative approaches, applying of artificial intelligence and machine learning to address a major public health challenge.
• Develop expertise applicable to careers indata science, physiology, or biochemistry.
• Become an active member of two prestigious research groups: HNERC and ICOS.
• Join thriving postgraduate research PGR communities.

Our ideal applicant will have:

• At least an upper-second-class (2:1) honours degree in a relevant subject, and have attained (or be close to completing) an MSc or MRes degree in a relevant discipline.
• Strong computational and analytical skills, including experience of working with large data sets, programming and applying artificial intelligence and/or machine learning.
• An interest in nutrition, ageing, and health.
• Strong critical thinking skills and an aptitude for problem solving and innovation.
• Motivation and independence, with the drive to undertake rigorous research, demonstrating initiative, autonomy, and responsibility.

Funding

Students who have, or are expecting to attain, at least an upper second-class honours degree (or equivalent) in a relevant subject, are invited to apply. Funding is available for Home (UK) students to cover tuition fees, a tax-free stipend at the UKRI rate (indicative amount in year 1 in 2026-27, £21,805) and research costs, for four years. Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates. There is no additional funding available to cover NHS Immigration Health Surcharge (IHS) costs, visa costs, flights etc.

Funding for this studentship is awarded on a competitive basis and is not guaranteed; availability will depend on the outcome of the selection process and subject to final approval by the University.

HOW TO APPLY

Please complete the following application form – Google Form

Applicants can only apply for 1 project; any additional applications will not be accepted.

Applicants should send the following documents to FMSstudentships@newcastle.ac.uk:

• a CV (including contact details of at least two academic (or other relevant) referees).
• a Cover letter – stating your project choice, as well as including additional information you feel is pertinent to your application.
• copies of your relevant undergraduate degree transcripts and certificates.
• a copy of your IELTS or TOEFL English language certificate (where required)
• a copy of your passport (photo page).

A GUIDE TO THE FORMAT REQUIRED FOR THE APPLICATION DOCUMENTS IS AVAILABLE

Please submit your documents in the following format only:

• each document should be submitted as a separate attachment and should be named as follows: candidate surname, candidate name – document type. For example: Jones, Jamie – CV; Jones, Jamie – cover letter.
• Please submit .pdf documents where possible for your CV, cover letter, transcripts and certificates. Do not submit photos of certificates.
• Do not combine documents into one pdf. You may zip separate documents into a zip file to send via email if required.
• When emailing your application, please use the email subject header: FMS PhD Application 2026

Applications not meeting these criteria may be rejected.

Informal enquiries may be made to the lead supervisor of the project you are interested in.

The deadline for all applications is 12 noon BST (UK time) on Wednesday 20th May 2026