Research Fellow (Quantitative) - Department of Applied Health Sciences - 106833 - Grade 8

University of Birmingham
Birmingham
3 days ago
Create job alert
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 September 2030


Closing date: 14th January 2026


Background

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


This post will sit within the Department of Applied Health Sciences and will support the delivery of the NIHR Research Professorship awarded to Professor Joht Singh Chandan (NIHR306365 https://fundingawards.nihr.ac.uk/award/NIHR306365). The Research Professorship aims to optimise the health sector response to violence against women and children by:



  • advancing multi-sector data linkage using Secure Data Environments
  • estimating the health and economic burden of violence
  • evaluating trauma-informed models of care
  • improving maternity outcomes and reducing inequalities
  • strengthening survivor engagement

This post will deliver the quantitative work package, WP2 ‘Estimating the burden associated with violence against women and children and trauma, using advanced epidemiology, multi-sector data linkage, statistical modelling and risk factor estimation’.


The post requires strong quantitative skills to support multi-level epidemiological analyses, causal inference, risk factor estimation, health inequalities modelling and complex dataset construction.


The Fellow will also contribute (as a secondary aspect) to aligned programmes within Professor Chandan’s portfolio, including the Hub for Health Inequalities, the NIHR Challenge: Maternity Disparities Consortium, and the NIHR Global Health Research Group (https://fundingawards.nihr.ac.uk/award/NIHR156915).


The role will involve planning and co-ordinating high-quality quantitative research, including advanced epidemiological analyses, health inequalities modelling, and SDE-based data linkage. The post holder will lead the analytical and quantitative components of WP2, including exposure–outcome modelling, risk estimation, and burden estimation (e.g., incident, DALY-like approaches, population-attributable fractions). The role will also contribute to development of a UK analytical hub connected to the GBD Europe initiative through quantitative risk factor estimation and model development.


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. This may include, where appropriate to the discipline:



  • Pursue personal research including developing research ideas and winning support, including financial support
  • Plan, publish and/or execute high quality quantitative research
  • Project manage research activities, and/or supervise other research staff
  • Present high quality findings in publications and conference proceedings
  • Develop novel statistical methodologies and techniques appropriate to multi-sector data integration and violence-related risk factor analysis
  • 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 relating to violence prevention, inequalities and trauma-informed care 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

Person Specification

  • Normally, a higher degree relevant to the research area (normally PhD in epidemiology, medical statistics, public health, data science, or similar) or equivalent qualifications
  • Extensive research experience and scholarship within applied quantitative methods, epidemiology, biostatistics, health data science, or related fields. Experience working with large, complex datasets (e.g., administrative data, linked datasets, health records)
  • 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 models, techniques and methods (e.g., regression modelling, causal inference, survival analysis, Bayesian approaches, risk factor estimation)
  • Extensive experience and achievement in knowledge transfer, enterprise and similar activity
  • Experience of championing Equality, Diversity and Inclusion in own work area
  • Ability to monitor and evaluate the extent to which equality and diversity legislation, policies, procedures are applied
  • Ability to identify issues with the potential to impact on protected groups and take appropriate action

DBS required

The University is committed to safeguarding and we promote safe recruitment practice, therefore all associated pre-employment checks will be undertaken before any appointment is confirmed. Due to the nature of the work undertaken in this role all successful applicants will be subject to a satisfactory DBS clearance prior to appointment.


Further particulars can be found here.


Informal enquiries to Joht Chandan, email:


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.


Equality, Diversity and Inclusion

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 everyone on our website.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analytics Research Fellow - Health Equity & Care Data

Associate Professorship (or Professorship) of Statistical Quantitative Finance/Financial Econom[...]

2026 | EMEA | London | FICC and Equities (Sales and Trading) Quantitative Strats | Summer Analyst

MSc Data Science and Artificial Intelligence

Senior Lecturer in Data Science

Senior Lecturer in Data Science

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.