Research Fellow - Department of Applied Health Sciences - 108058 - Grade 8 in Birmingham

Description

Position Details

Department of Applied Health Sciences, School of Health Sciences, College of Medicine and Health

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £47,389 to £56,535 with potential progression once in post to £63,606

Grade: 8

Full Time, Fixed Term contract up to November 2027

Closing date: 8^th October 2026

Background

To create and disseminate knowledge through initiating and conducting original research and through publication, as appropriate to the disciplinary area.

The NIHR Biomedical Research Centre (BRC) Birmingham is £30million infrastructure award to support translation of scientific discoveries into treatments and diagnostics to improve people’s health in the UK and across the globe. The BRC Data, Diagnostics and Decision Tools theme focusses on the use of healthcare data and data analytics to accelerate the benefits of data-driven discovery, translation and digital innovation for patients and communities.

The postholder will work with routinely collected primary and secondary healthcare data, with a particular focus on acute care data. Routinely collected acute care data in the UK is fragmented across multiple clinical systems, including emergency departments, acute inpatient services, diagnostics, electronic prescribing, and other hospital and outcome datasets. These systems use different data structures, coding systems and identifiers, including SNOMED CT, ICD-10 and OPCS-4. Transforming these routinely collected data into a common data model would enable standardised, interoperable and reproducible analyses, supporting the efficient scaling of research across datasets, clinical settings and NHS organisations.

The postholder will lead the design and development of a novel, harmonised data model and research-ready acute care database that integrates routinely collected data from hospital information systems (e.g. PICS, Cerner), alongside relevant diagnostic, prescribing, laboratory and outcome datasets, within a secure data environment. They will support and contribute to research, to generate high-quality, reproducible real-world evidence rapidly and at scale. They will conduct and publish original methodological and applied research arising from this work and act as a primary interface between clinical and academic researchers, NHS Trust informatics teams and information governance functions.

This data transformation will enable rapid recalibration and deployment of risk prediction models. To achieve this, the postholder will also lead methodological work focused on evaluating, externally validating and recalibrating clinical prediction models using routinely collected healthcare care data, particularly acute care. This will include developing reproducible data pipelines to identify and harmonise predictor variables and outcomes, assessing model performance and clinical utility across different patient populations and care settings, and prototyping approaches for implementing validated models within secure data environments.

The post is a FTC role offered initially until 30th November 2027.

Role Summary

• Initiate and conduct original research which has measurable outcomes and is reflected in a growing national and often incipient international reputation
• Plan, design and co-ordinate research activities and programmes
• Contribute to the development of research strategies
• Publish results of own research
• Supervise PhD students
• Contribute to the Department/School through management/leadership
• Develop and make substantial contributions to knowledge transfer, enterprise, business engagement, public engagement activities, widening participation, schools outreach or similar activities at Department/School level or further within the University

Main Duties

• To plan and carry out research, using appropriate methodology and techniques appropriate to the discipline:
  • Design, develop and maintain data pipelines and extract-transform-load (ETL) processes to acquire, clean, link and standardise routinely collected primary care, inpatient, outpatient and emergency care data from sources such as PICS, Cerner and related NHS systems and data providers
  • Design and implement a novel, harmonised research data model and database schema for acute care data, applying data modelling and database design best practice to ensure efficient, well-documented and reproducible data storage and retrieval
  • Develop and maintain scalable, secure data infrastructure to support data storage, processing and analysis for acute care research within a secure data environment to enable rapid, reproducible epidemiological research by consortium investigators
  • Develop methods and automated pipelines for external validation and recalibration of prediction models using routinely collected healthcare data
• Pursue personal research including developing research ideas and winning support, including financial support
• Plan, publish and/or execute high quality research
• Project manage research activities, and/or supervise other research staff
• Present high quality findings in publications and conference proceedings
• Develop novel methodologies and techniques appropriate to the type of research being pursued
• Supervise and examine PhD students, both within and out with the University
• Provide expert advice to colleagues and students within discipline
• Contribute to the administration/management of research across the Department/School
• Develop and make substantial contributions to knowledge transfer, enterprise, business engagement, and public engagement activities of manifest benefit to the College and the University
• Contribute to some administrative activities within the University, typically relating to research
• Apply knowledge in a way that develops new intellectual understanding *
• Actively manages equality, diversity and inclusion through monitoring and evaluation and actively challenging unacceptable behaviour in line with university policies
• Other relevant criteria from our equality and diversity duties document.

* This indicative responsibility may also be included in a research role at a lower grade.

Person Specification

• A PhD relevant to the research area (or near completion), or equivalent PhD- level qualifications or extensive professional experience in healthcare data.
• Extensive research experience and scholarship within subject specialism to include:
  • data engineering and statistical analysis, with strong programming skills in SQL, Python, R and other relevant languages for use in research
  • in-depth knowledge of UK healthcare data, including primary care data, and NHS secondary and tertiary care electronic patient records and information systems (e.g. PICS, Cerner), and of related data and interoperability standards in a research context
  • Expertise in advanced data modelling and engineering applied to complex NHS electronic health record data, a strong grounding in clinical prediction modelling and health informatics research methods
  • Demonstrable understanding of data security and information governance principles and practice in a health setting (e.g. UK GDPR, Caldicott principles, NHS Data Security and Protection Toolkit, secure data environments/trusted research environments)
  • Experience with cloud-based or secure research data platforms (e.g. Azure, AWS, NHS secure data environments)
  • Experience of risk prediction modelling, including development, recalibration and validation, and relevant statistical methods
• Experience and achievement reflected in a growing reputation
• Extensive experience and demonstrated success in planning, undertaking and project managing research to deliver high quality results
• Extensive experience of applying and/or developing and devising successful data models, techniques and methods such as data models, database schemas, data pipelines and ETL processes for large, complex healthcare datasets.
• Extensive experience and achievement in knowledge transfer, enterprise and similar activity
• Ability to identify issues with the potential to impact on protected groups and take appropriate action
• Other relevant criteria from our equality and diversity knowledge, skills and experience document.

Further particulars can be found here

Informal enquiries to Nicola Adderley, email: n.j.adderley@bham.ac.uk

Use of AI in applications: We want to understand your genuine interest in the role and for the written elements of your application to accurately reflect your own communication style. Applications that rely too heavily on AI tools can appear generic and lack the detail we need to assess your skills and experience. Such applications will unlikely be progressed to interview.

We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. You can find out more about our work to create a fairer university for everyoneon our website.