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Research Associate Mathematical Biomedicine

The University of Manchester - Division of Diabetes, Endocrinology & Gastroenterology

Location: Manchester, Hybrid
Salary: £37,694 to £46,049 UoM Grade 6
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 12th January 2026
Closes: 6th February 2026
Job Ref: BMH-030380

We are excited to offer this opportunity to a highly motivated Research Associate to join an ambitious new team working in the field of Digital Endocrinology. The successful applicant will conduct original research aimed at understanding variability in circadian hormone profiles in humans, uncovering fundamental insights into endocrine function and supporting the diagnosis and management of endocrine conditions. The position is funded through a UKRI Future Leaders Fellowship awarded to Dr Eder Zavala: “Developing a mathematical and computational framework for digital endocrinology”. The work will build on hormonal time series data collected at unprecedented time resolution in healthy humans and in patients, including studies in real life settings with a state-of-the-art wearable device (https://www.science.org/doi/abs/10.1126/scitranslmed.adg8464).

We are seeking to appoint a creative and enthusiastic individual who will lead on projects modelling the mechanisms behind hormonal rhythm misalignment. The models will be used to predict dynamic responses to stressors, sleep disruptions, and diagnostic tests, as well as the long-term changes that occur during disease. A key challenge of your work will be accounting for the variability in hormonal rhythms observed across individuals. To characterise this variability, you will take advantage of unique in its kind datasets and advanced mathematical and computational methods and help develop personalised models. The practical element of your project will be based on, but not limited to, Ordinary and Delay Differential Equations, bifurcation analyses, Bayesian inference, and Machine Learning methods.

In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as well as with an international team of collaborators including clinicians, computer scientists, and mathematicians. The team is dynamic and ambitious as well as being welcoming and supportive.

The applicant should have experience with mathematical modelling using ODEs and/or DDEs, parameter estimation methods and HPC simulations. The applicant should be familiar with dynamical systems theory, network analysis and Bayesian inference frameworks.

The vacancy is for a full-time post available from 1st April 2026 with a contract of 36 months.

What you will get in return:

  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.

Please be aware that due to the number of applications we unfortunately may not able to provide individual feedback on your application.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr Eder Zavala - UKRI Future Leaders Fellow

Email: eder.zavala@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

0161 850 2004 https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

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