Snabbfakta

    • Manchester

Ansök senast: 2024-11-22

Research Associate in Medical Statistics

Publicerad 2024-09-23

We are seeking a Research Associate in medical statistics with specific expertise in prediction modelling, causal inference and/or equity/fairness. The role holder will be involved with a range of projects including “Assessing and Predicting Risks of Valproate withdrawal and counterfactual risks in people with Epilepsy” in which we seek to use observational data to emulate a ‘target trial’ to infer the causal effect of valproate withdrawal in young patients with epilepsy; and Investigating equity and fairness in a personalised renal function monitoring tool, in which we will undertake research into the fairness implications of a clinical prediction model being used to monitor renal function in patients with heart failure.

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.

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.

What you will get in return:

  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers

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: https://www.bmh.manchester.ac.uk/about/equality/

Our University is positive about flexible working you can find out more here

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr David Jenkins

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

Tel: 0161 306 7629

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.

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