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Job Number
SU00265
Contract Type
Fixed Term
Salary
£38,205 to £44,263 per annum
Faculty/Directorate
Faculty of Medicine, Health and Life Science
Location
Singleton Campus, Swansea
Closing Date
6 May 2024
Interview Date
17 May 2024
Informal Enquiries

About The University

Swansea University is a research-led university that has been making a difference since 1920. The University community thrives on exploration and discovery and offers the right balance of excellent teaching and research, matched by an enviable quality of life.

Our stunning waterfront campuses and multicultural community make us a desirable workplace for colleagues from around the world. Our reward and benefits, and ways of working enable those who join us to have enriching careers, matched by an excellent work-life balance.

About The Role

This is a Fixed Term contract until 31st March 2028.

The Health Data Research (HDR) UK Medicines in Acute and Chronic Care Driver Programme is a UK-wide multidisciplinary collaboration of clinical, data and discovery scientists focussed on delivering innovative data science solutions for medicines management. This 4-year Programme will develop and apply statistical methods using large linked electronic health records to identify adverse drug reactions, errors in prescribing, drug-drug interactions and improve patient outcomes through increased guideline compliance and addressing a series of clinically informed, data-driven challenges.

As a core partner of the HDR UK Medicines in Acute and Chronic Care Driver Programme, the Population Data Science group at Swansea University will utilise the Secure Anonymised Information Linkage (SAIL) Databank’s (https://saildatabank.com/) rich anonymised population-scale, individual-level, linked data sources to answer important population-level questions that will inform health technology assessment, policy, and practice.

We are looking for a statistician/data scientist who will lead and undertake advanced analysis methods to deliver the research priorities of the programme. Activities will include (but not limited to) analysis of large-scale, linked, electronic health records including application of generalised linear models, survival analysis, simulation-based approaches, and evidence synthesis methods. The post holder will work closely with a team of senior researchers and data scientists within the Population Data Science group under the leadership of Professor Rhiannon Owen as well as various external stakeholders and organisations as part of a UK-wide collaborative.

The Research Officer will be based within the Population Data Science group at Swansea University (https://popdatasci.swan.ac.uk/), which is home to leading Researchers & Data Scientists who focus on a range of projects and programmes that seek to improve people's lives through population data science research.

Applications are sought from individuals with skills and experience in data analysis with a background in any of the following areas/backgrounds: statistics, mathematics, operational research, or related data science disciplines.

Equality, Diversity & Inclusion

The University is committed to supporting and promoting equality and diversity in all its practices and activities. We aim to establish an inclusive environment and welcome diverse applications from the following protected characteristics: age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (including colour, nationality, ethnic and national origin), religion or belief, sex, sexual orientation.

As an inclusive and welcoming workplace, we value people for their skills regardless of their background. Applications are welcome in Welsh and will not be treated less favourably than those submitted in English.

We have an under-representation of men in the area of research and would particularly welcome applications from men for this position. We also have an under representation of individuals from ethnic minority backgrounds and would encourage applications from these groups. Appointments will always be made on merit.

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