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Research Associate in Medical Statistics

The University of Manchester - Biology, Medicine Health - Division of Informatics, Imaging & Data Science - School of Health Sciences

Location: Manchester
Salary: £36,924 to £45,163 per annum, dependent on relevant experience
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 16th January 2025
Closes: 27th January 2025
Job Ref: BMH-027794

Job reference: BMH-027794
Salary: £36,924-£45,163 per annum, dependent on relevant experience
Faculty/Organisational unit: Biology, Medicine Health
Location: Oxford Road
Employment type: Fixed Term
Division/Team: Division of Informatics, Imaging & Data Science
Hours per week: Full time (1 FTE)
Closing date (DD/MM/YYYY): 27/01/2025
Contract duration: Fixed term until 30th June 2026
School/Directorate: School of Health Sciences

We are seeking a Research Associate in medical statistics – with specific expertise in prediction modelling and use of electronic health records. The role holder will be involved with a range of projects – including “CanCYP: a tool to enable cancer risk prediction in children and young people with a cancer predisposing gene alteration” in which we will use real world health data to develop a clinician facing decision support tool. There is currently an unmet but critical need to have better second primary cancer risk data so that appropriate surveillance/early detection measures can be put in place. This project will integrate the National Cancer Registry (NCRAS) with NHS germline genomics lab data. We will then develop and validate models to predict primary cancer risks in children and young people and produce a clinician-facing cancer risk calculator.

You will join an engaged data science community at Manchester with of over 400 investigators working across the University in different disciplines allied to data sciences and connected through the Institute for Data Science and Artificial Intelligence. Our expertise covers the complete data science life-cycle: from information management, through analytics, to practical applications. A key feature of our approach is very close coupling between methodologists and translational scientists, drawing on strength-in-depth in real-world applications of data science. This creates a virtuous circle, where challenging real-world problems drive the methodology research agenda, whilst providing a natural route to exploiting new algorithms and methods. We believe this deeply multidisciplinary approach is one of the distinctive features of data science at Manchester. Manchester is a member of The Alan Turing Institute: the UK’s national institute for data science, and researchers at Manchester lead a Turing research programme in health.

The School is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. An appointment will always be made on merit. For further information, please visit: www.bmh.manchester.ac.uk/about/equality

As this role involves research at a postgraduate level, applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI.                                                

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr David Jenkins

Email: david.jenkins-5@manchester.ac.uk

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