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PhD Studentship - Addressing Challenges in Investigating the Relationships between Environments and Healthy Ageing

Newcastle University

Qualification Type: PhD
Location: Newcastle upon Tyne
Funding for: UK Students, EU Students, International Students
Funding amount: £20,780
Hours: Full Time
Placed On: 26th March 2025
Closes: 27th April 2025
Reference: PH059

Award Summary

100% of home tuition fees paid and annual living expenses at UKRI rate, currently £20,780 per year. A research training support grant of £5,000 per year is available to cover research costs (e.g. data costs) and local/national/international travel (e.g. conferences).

Successful international candidates will be required to fund the difference between the home fees and international fees.

Overview

This project will focus on investigating the environmental impact on disability and health in older people and addressing methodological challenges related to quantitative analysis. Based on the World Health Organization, healthy ageing is defined as ‘the process of developing and maintaining the functional ability that enables wellbeing in older age’ and is made up of the interaction between intrinsic capacity (individual’s physical and mental conditions) and the environment (the context of an individual’s life). To investigate how the environment can support healthy ageing, recent epidemiological research has highlighted the potential for integrating geospatial data (e.g., green spaces, local services) and ageing cohorts and investigating the relationships between environmental factors and health conditions in older people. However, there are many methodological challenges, including multiple issues in statistical (longitudinal analysis, measurement errors), epidemiological (confounding effects, selection bias) and ageing research (loss to follow-up, mortality). The PhD student will utilise interdisciplinary data sources of environmental data and cohort studies and choose to investigate some of these issues based on their interests.

Number of awards: 1

Start date: September 2025

Award duration: 3 years full time. 

Sponsor: Newcastle University 

Supervisors

Dr. Yu-Tzu Wu, Dr. Andrew Kingston (Population Health Sciences institute) 

Eligibility criteria

Applicants should possess a minimum 2:1 degree in statistics, epidemiology, public health, data sciences, mathematics or a related field that includes a substantial quantitative analysis component. While a Master's degree in a relevant subject with Merit or higher is preferred, it is not mandatory. Candidates must be eager to develop advanced epidemiological and statistical analysis abilities. A keen interest in healthy aging research is crucial. Familiarity or experience with statistical software (e.g., Stata, R) is a plus. If your first language is not English you need an overall IELTS score of 6.5 (at least 5.5 in all sub-skills) or equivalent language qualification.

How to apply

You must apply through the applyto.newcastle.ac.uk/SignIn by creating an account.

All relevant fields should be completed, but fields marked with a red asterisk must be completed. The following information will help us to process your application. You should:

  • Click on programme of study.
  • Insert 8370F in the programme code section and click search.
  • Select Programme name PhD in the Faculty of Medical Sciences(full time) - Health Services Research.
  • Insert PH059 in the studentship/partnership reference field.
  • Attach a covering letter and CV. The covering letter must state the title of the studentship. Please quote reference code PH059 and state how your interests and experience relate to the proposed project.
  • Attach degree transcripts* and certificates and, if English is not your first language, a copy of your English language qualification. 
  • Non-UK candidates must contact phsipgenquiries@newcastle.ac.uk regarding eligibility for home fees.

*You will not be able to submit your application until you have submitted your degree transcript/s. 

Contact Details

Yu-Tzu Wu (yu-tzu.wu@newcastle.ac.uk)  

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