Population and Health Data Science: Fully Funded Health Data Research UK PhD Scholarship: Use of Real-World Evidence in Health Technology Assessment for Multiple Long-term Conditions

Job title:

Population and Health Data Science: Fully Funded Health Data Research UK PhD Scholarship: Use of Real-World Evidence in Health Technology Assessment for Multiple Long-term Conditions

Company

Swansea University

Job description

Job Information Organisation/CompanySwansea University DepartmentCentral Research FieldMedical sciences Researcher ProfileFirst Stage Researcher (R1) CountryUnited Kingdom Application Deadline12 May 2024 – 23:59 (Europe/London) Type of ContractOther Job StatusFull-time Is the job funded through the EU Research Framework Programme?Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure?NoOffer DescriptionFunding provider:Subject areas:Project start date:

• 1 October 2024 (Enrolment open from mid-September)

Project supervisors:

• Professor Rhiannon Owen (

) * Dr James Rafferty

• Professor Hamish Laing
• Professor Keith Abrams (University of Warwick)

Aligned programme of study: PhD in Population and Health Data ScienceMode of study: Full-timeProject description:Healthcare decision-making has previously focussed on developing recommendations for single conditions. However, standardised care for each chronic condition in isolation can be inappropriate for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a modelling framework to estimate the natural history of disease in individuals living with multiple long-term conditions using population-scale, linked, electronic health records from the Secure Anonymised Information Linkage (SAIL) Databank Wales Multimorbidity e-Cohort ( ). This approach will allow estimation of the potential adverse effects (such as hospitalisations) of drug-on-drug interactions for the treatment of multiple conditions and associated genetic, environmental, or demographic risk factors. Further this PhD project will compare the efficacy of different combinations of treatments used in people with multiple long-term conditions, and assess potential health inequalities.FacilitiesThe PhD student will be based in Population Data Science at Swansea University with visiting PhD Student Status at the Department of Statistics at the University of Warwick, benefiting from the stimulating and supportive environment and bespoke training programmes. The successful candidate will receive training to develop their knowledge and expertise in statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student will have the opportunity to present their work at national and international conferences and workshops.This PhD is funded as part of the HDR UK Medicines in Acute and Chronic Care Driver Programme, which is a national collaboration that aims to understand and transform the use of medicines for patient benefit, and reduce medicines-associated harm. The Driver Programme has a particular focus on vulnerable populations including people living with multiple long-term conditions and those experiencing health inequalities. The successful candidate will be one of several PhD students contributing to the wider HDR UK Driver Programmes and will have the opportunity to collaborate with the wider HDR UK Driver Programme Team as well as access additional training and associated events hosted by HDR UK.RequirementsResearch Field Medical sciences Education Level Bachelor Degree or equivalentSkills/QualificationsCandidates must hold an Upper Second Class (2.1) honours degree. Candidates will need an MSc in Statistics/Biostatistics or Epidemiology/Health Data Science (with a strong analytical component) plus programming and data analysis skills/experience in R and/or Python.If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.Specific RequirementsExperience of analysing large-scale linked electronic health record data and knowledge of Bayesian methods would be an advantage.This scholarship is open to candidates of any nationality.Additional InformationBenefitsThis scholarship covers the full cost of tuition fees and an annual stipend of £19,237.Additional research expenses will also be available.Eligibility criteriaCandidates must hold an Upper Second Class (2.1) honours degree. Candidates will need an MSc in Statistics/Biostatistics or Epidemiology/Health Data Science (with a strong analytical component) plus programming and data analysis skills/experience in R and/or Python.Experience of analysing large-scale linked electronic health record data and knowledge of Bayesian methods would be an advantage.If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.This scholarship is open to candidates of any nationality.Selection processPlease visit our website for more information.Website for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Swansea University Country United Kingdom GeofieldWhere to apply WebsiteContact State/ProvinceSwansea CitySwansea WebsiteStreetSingleton Park Postal CodeSA2 8PPSTATUS: EXPIRED

Expected salary

£19237 per year

Location

United Kingdom

Job date

Sun, 21 Apr 2024 04:01:08 GMT

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