Research Associate - Department of Applied Health Sciences - 106111 - Grade 6

University of Birmingham; Birmingham; On-site; GBP 32,000 - 36,000; Full time

Job summary

A leading UK university is seeking a motivated researcher in statistics and machine learning to join its Department of Applied Health Sciences. This role involves developing new methods for randomized trials related to vector-borne disease control. The successful candidate will have a strong quantitative background and will contribute to interdisciplinary research projects with international collaborations. Salary ranges from £32,546 to £35,116, with opportunities for growth.

Qualifications

• Experience in implementing mathematical or statistical models desirable.
• Ability to work both as a team and independently.
• Experience working with health-related data is advantageous.

Responsibilities

• Develop and test new methods for trial design and analysis.
• Contribute to generating academic publications.
• Disseminate research findings for publication.

Skills

Strong mathematical and quantitative skills

Familiarity with statistical analysis software

Ability to communicate complex information clearly

Education

BSc (Hons)/Masters level

Tools

Stata

R

Python

C++

Job 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 £32,546 to £35,116 with potential progression once in post to £39,355

Grade: 7

Full Time, Fixed Term contract up to August 2028

Closing date: 17th August 2025

Please note: We are advertising for both a Research Associate (106111) and a Research Fellow (106065), however there is only 1 post available.

Background

We are seeking a highly motivated researcher in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project looking at the design and analysis of randomised trials of interventions to reduce the risk of vector-borne diseases (e.g. malaria and dengue). The Project offers an interdisciplinary opportunity to work in at the intersection of statistics and epidemiology, and features an exciting case study involving novel GM and gene drive interventions for control of malaria-transmitting mosquitoes, with opportunities to build an international research portfolio.

The postholder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised trial designs and working with infectious disease models. You will work within a multidisciplinary team with close links to Imperial College London and the Ifakara Health Institute in Tanzania, including clinicians, epidemiologists, and statisticians. Your work will contribute to a supporting the design of upcoming first field trials of novel technologies in infectious disease control.

This role is particularly suited to candidates with a strong quantitative background. We welcome applicants with training in mathematics, statistics, health economics, computer science, or epidemiology, particularly those with good numeracy and a strong interest in applied health research. We do not require a previous background in the topic area of the post, and training and support will be provided to develop skills in the appropriate area. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous. The ability to work independently, manage multiple tasks, and communicate findings clearly is essential.

About the Project:

Novel GM interventions for mosquito control could represent a step change in progressing towards elimination of the world’s most harmful vector-borne diseases, including malaria and dengue. However, conducting field trials of such interventions is challenging due to complex logistics and uncertain outcomes. We aim to develop novel methodological strategies that can reduce the resource requirements to rigorously evaluate new and uncertain community-level interventions in infectious disease control. A key component relates to harnessing advanced mechanistic disease transmission models to improve prediction of clinical trial outcomes (e.g. doi: 10.1038/s41467-024-53065-z). Given the uncertainty associated with intervention outcomes, we also aim to explore adaptive trial designs to enable studies to start small and refine their design as they progress. We will work closely with co-investigators from the Ifakara Health Institute (Tanzania) to ensure the methods are feasible and implementable in disease-endemic settings, and to improve impact. The project will involve a series of stakeholder engagement workshops, with opportunities for travel to Tanzania.

Role Summary

• Work with the study investigators (Prof. Sam Watson (University of Birmingham), Dr Penelope Hancock (Imperial College London) and Prof. Fredros Okumu (University of Glasgow/Ifakara Health Institute) to develop and test new methods for trial design and analysis.
• Developing statistical models and code to run the proposed methods.
• Developing and running simulation-based analyses of the new methods.
• Contribute to generating academic publications and reports.
• Contribute to public and stakeholder engagement workshops

Main Duties

The responsibilities may include some but not all of the responsibilities outlined below.

• Contribute to the development, documentation, and testing of new statistical methods.
• Develop code to run and evaluate statistical models, with the support of project supervisors.
• Support writing of research outputs for academic and lay audiences, and contribute to the development and running of stakeholder engagement activities in African countries.
• Disseminate research findings for publication, including research seminars and conferences.
• Contribute to Departmental/School research-related activities and research-related administration.
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader.
• Deal with problems that may affect the achievement of research objectives and deadlines
• Promote equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

• BSc (Hons)/Masters level (Grade 6) applicants with a strong relevant skill set will also be considered.
• Strong mathematical and quantitative skills.Experience in the implementation of mathematical or statistical models and model fitting is desirable but not essential.
• Familiarity or experience ofusing Stata, R, Python, or similar. Knowledge of C++ would be advantageous but not essential.
• Ability to communicate complex information clearly.
• Excellent ability to work as a team and independently including co-ordinating own work with others to avoid conflict or duplication of effort.
• Understanding of and ability to contribute to broader management/administration processes.
• Contribute to the planning and organising of the research programme and/or specific research project.

Further particulars can be found here

Informal enquiries to Samuel Watson, email: [e-mail]

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