Research Assistant in Machine Learning Epidemiology

Research Assistant in Machine Learning for Epidemiology

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Job Description

Job Title:

Research Assistant in Machine Learning for Epidemiology Posting

Start Date:

13/10/2026 Job  School/Department:
Computer Science Work Arrangement:
Part Time (Hybrid) Contract Type:
Fixed-term Salary per annum (£): £32,080 pro rata Closing Date: 08/11/2026

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more about our benefits (opens in a new window) and join us to become part of something special.

Overview

Strep A is a common bacterial infection that causes spectacular, unexpected outbreaks of disease every few years. The cause of these outbreaks is unknown, but several factors are likely to contribute, for example, the burden of circulating viral infections. This project strives to develop an artificial intelligence (AI)-driven early warning system to predict the risk of Strep A outbreaks and upsurges before they occur.

The RA will work to integrate multiple datasets and apply a combination of mathematical modelling methods, including time-series modelling and probabilistic machine learning. Anticipated work includes developing and training models, with validation and refinement steps using retrospective data and simulation work undertaken where appropriate. This will be followed by a further evaluation phase to assess model performance, usability, and potential for real-world application using prospective data.

Main duties and responsibilities

• Collate, clean and prepare epidemiological datasets from a range of sources, ensuring data quality.
• Apply and help develop machine learning models, including feature preparation, model selection, fitting, and hyperparameter tuning.
• Conduct exploratory data analysis and produce descriptive statistics and clear visualisations.
• Contribute to model evaluation and validation, including selecting appropriate performance metrics demonstrating model generalisability to the real world.
• Ensure all activities comply with data protection legislation, research ethics requirements, and information governance procedures for handling sensitive health data.
• Work proactively and on own initiative, responding constructively to feedback from the line managers / principal investigators.
• Carry out other duties, commensurate with the grade and remit of the post.

Person Specification

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

Criteria

Essential or desirable

Stage(s) assessed at

An undergraduate degree in a quantitative discipline such as data science, statistics, computer science, mathematics, epidemiology or a closely related field .

Essential

Application

Demonstrable programming skills in Python, including common data science / machine learning libraries (eg pandas, scikit-learn or PyTorch/JAX).

Essential

Application/interview

Working knowledge of core machine learning methods (eg regression, classification, clustering).

Essential

Application/interview

Experience in cleaning, wrangling, and preparing structured datasets for analysis

Essential

Application/interview

Experienced in data visualisation and version control.

Essential

Application/interview

Good written and verbal communication skills.

Essential

Interview

Ability to work independently, prioritise and meet deadlines within limited weekly hours with minimal supervision.

Desirable

Interview

Awareness of data governance, confidentiality, and the ethical handling of sensitive health data.

Desirable

Interview

Further Information

Grade

Grade 6

Salary

£32,080 pro rata (equivalent to a full-time salary), with an actual salary of £6,416 based on seven hours a week

Work arrangement

Part-time

Duration

Until 31st August 2027

Line manager

Academic Fellow in AI for Health and…