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Raithby Studentship: PhD in Health Data Science

  • Full or part time
  • Application Deadline
    Friday, December 06, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

This scholarship provides an opportunity to develop and apply novel methods for the analysis of health data to explore the interaction between physical and mental health.

Data captured routinely when providing healthcare have the potential to drive understanding and improve treatment decision making by facilitating analysis of a potentially wide range of conditions, for large and diverse patient populations, over significant time periods. Accessing such data requires an appropriate legal and ethical basis, and robust analytical methods that jointly consider clinical, statistical and technical dimensions are needed. With all these requirements in place, such data can be used to study populations, interventions and outcomes where conventional methods of research data collection may not be practicable or would introduce significant biases.

Increasing numbers of adults are living with multiple health conditions that span their physical and mental health. Individual conditions are subject to improvement and deterioration over time, and may influence (and be influenced by) other co-occurring conditions. For example, deterioration in a mental health condition may lead to deterioration in a musculoskeletal condition due to a reduction in physical exercise, which ultimately leads to an increase in frailty. Understanding how physical and mental health conditions progress over time and influence one another is an important factor in determining effective and efficient patient care.

Your work will be supported by a multi-disciplinary team within the Leeds Institute of Health Sciences (LIHS) comprising of statisticians, computer scientists and clinicians. You will have the opportunity to contribute to and build on existing work within LIHS, including work which is exploring the interactions between musculoskeletal conditions, frailty, and depression. You will also have the opportunity to develop your own areas of technical and clinical interest over time.

Eligibility:
You should hold a first degree equivalent to at least a UK upper second class honours degree in a numerate discipline, such as Computer Science, Mathematics or Engineering. You will have excellent programming/scripting skills and an ability to understand and develop robust solutions to complex problems. You will also have excellent communication skills and the ability to work effectively with colleagues from a variety of disciplines. Knowledge of the health domain is desirable but not essential.

The Faculty minimum requirements for candidates whose first language is not English are:
• British Council IELTS – score of 6.5 overall, with no element less than 6.0
• TOEFL iBT – overall score of 92 with the listening and reading element no less than 21, writing element no less than 22 and the speaking element no less than 23.

How to apply:

To apply for this project applicants should complete a Faculty Scholarship Application form using the link below https://medicinehealth.leeds.ac.uk/downloads/download/78/fmh_scholarship_application_form_2018_2019 and send this alongside a a full academic CV, degree certificates and transcripts (or marks so far if still studying) to the Faculty Graduate School at

We also require 2 academic references to support your application. Please ask your referees to send these references on your behalf, directly to by no later than Friday 6 December 2019.

Any queries regarding the application process should be directed to .

Funding Notes

Raithby Scholarships are available for UK and EU citizens only. These scholarships will attract an annual tax-free stipend of £15,009 for up to 3 years, subject to satisfactory progress and will cover the UK/EU academic fees.

References

*See https://discover.dc.nihr.ac.uk/content/signal-00572/multi-morbidity-predicted-to-increase-in-the-uk-over-the-next-20-years
** See https://academic.oup.com/ageing/article/45/3/353/1739750

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