We are seeking to appoint a highly motivated and skilled Postdoctoral Researcher to develop methods for informing personalised treatment programmes for Cystic Fibrosis (CF) patients. The objective is to improve patient outcomes, minimise treatment burden and minimise the emergence of antimicrobial resistance. You will work with experimental data and patient data, including sequencing data. You will develop and use data science techniques including machine learning and mathematical modelling. The role sits within a highly interdisciplinary research hub supported by a multi-million-pound investment from the cystic fibrosis trust.

The position will be hosted in the Department of Mathematical Sciences at the University of Liverpool and will include regular interaction with the wider CF hub including clinicians and collaboration with IBM. We expect that a hybrid approach interweaving machine learning with more traditional mechanistic modelling methods will prove to be valuable.

Key responsibilities and duties:
Use data science methods together with patient and experimental data to inform personalised treatment for CF patients.
Interact with the wider CF hub and national CF networks as required.
Publish research findings in peer-reviewed journals and present at conferences.
Communicate and collaborate effectively with colleagues within and outside the immediate team, including end-users and stakeholders.

The post will be available from 1 January 2025 and will run for 18 months from the date of appointment. You should have a PhD (or close to completion) in Applied Mathematics, Physics or similar numerate subject. For informal inquiries about the position, please contact Professor Kieran Sharkey, (kjs@liverpool.ac.uk).