Research Associate (Real-World Evidence) (Fixed Term)
University of Cambridge, Newtown, Cambridge
Research Associate (Real-World Evidence) (Fixed Term)
Salary not available. View on company website.
University of Cambridge, Newtown, Cambridge
- Full time
- Temporary
- Onsite working
Posted today, 22 Dec | Get your application in now to be one of the first to apply.
Closing date: Closing date not specified
job Ref: 6ae09046653c45338906ffc0b59a6608
Full Job Description
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
We wish to appoint a Research Associate to design, execute and report the results of real-world data analytic studies in mental healthcare as part of a National Institute for Health and Care Research (NIHR) programme to improve clinical outcomes in people with mental disorders. The aim of the research programme is to develop Real World Evidence (RWE) that will be implemented in clinical practice to reduce treatment delays and improve access to NHS mental healthcare.
The appointee will work with a multidisciplinary team of data engineers, clinicians and data analysts to lead epidemiological research on largescale electronic datasets and generate evidence to improve mental healthcare outcomes.
The team conducts research using de-identified EHR data acquired through the Clinical Records Anonymisation and Text Extraction (CRATE) and Clinical Record Interactive Search (CRIS) tools which enable the assembly of data from patients receiving mental healthcare in UK NHS mental health trusts. The research will involve leading multi-centre epidemiological studies whose findings will inform future NHS mental healthcare service policy.
The research programme is led by Dr Rashmi Patel (Assistant Professor in Real-World Data Analytics), an NIHR Advanced Fellow who has completed several research studies to investigate clinical outcomes in mental disorders using real-world data derived from EHRs, and will be in collaboration with Dr Rajeev Krishnadas (Assistant Professor in Psychosis Studies) who has expertise in predictive and causal modelling and is pursuing the use of virtual wards in psychiatry.
The appointee will have a unique opportunity to develop skills in mental health research, epidemiology and healthcare service research using state-of-the-art clinical informatics methods such as natural language processing (NLP), machine learning and Bayesian statistics. The appointee will be expected to lead the writing of research protocols and ethics applications, publications in peer-reviewed journals, conference abstract and grant applications. They will join a highly productive research department with the opportunity to develop applications for independent postdoctoral research funding. The role will be hybrid with office work based at the Department of Psychiatry, Cambridge Biomedical Campus.