University of Bristol
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4 days ago
Funded PhD in Artificial Intelligence for Fungal Susceptibility Prediction in Clinical Diagnostics University of Bristol in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Funded through the GW4 BioMed3 MRC Doctoral Landscape Programme. Covers UK tuition fees and a Doctoral Stipend matching the UK Research Council National Minimum (£21,805 p.a. for 2026/27, updated each year). Additional research training and support funding of up to £5,000 per annum is available.
Deadline
Oct 21, 2026
Country
United Kingdom
University
University of Bristol

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About this position
Funded PhD project at the University of Bristol within the GW4 BioMed3 MRC Doctoral Training Partnership: Artificial intelligence to identify fungal susceptibility in the clinical diagnostic laboratory.
This interdisciplinary studentship sits at the intersection of bioinformatics, data science, machine learning, medical science, and clinical mycology. The project aims to develop in-silico predictors of antifungal susceptibility for clinically important fungal pathogens using MALDI-ToF mass spectrometry, spectral deconvolution, and novel AI/representative learning approaches. The student will work with historic acquisitions linked to antimicrobial susceptibility test results and explore how sample preparation and acquisition parameters can be optimized to improve model performance.
The project is embedded within the UKHSA National Mycology Reference Laboratory, giving access to clinical processes, procedures, and a comprehensive archive of samples, genetic data, and MALDI-ToF data. There is also an opportunity to visit collaborators at the University of Cape Town to adapt and tune models for LMIC applications, including azole-resistant Aspergillus fumigatus in cystic fibrosis patients.
Applicants from a range of backgrounds are welcome. The team will consider students with mathematical/computational training who want to learn bioinformatics and laboratory work, as well as biological/biomedical applicants who want to build skills in programming, data science, and machine learning. The preparatory period includes reading and training in antimicrobial resistance, clinical mycology, and the diagnostic landscape, plus shadowing clinical microbiology teams.
Funding: UK tuition fees plus a doctoral stipend matching the UK Research Council National Minimum (£21,805 p.a. for 2026/27, updated annually), with additional research training and support funding of up to £5,000 per year.
Application deadline: 21 October 2026, 5:00 pm. Shortlisted candidates are notified from 22 December 2026, interviews are held virtually on 26–27 January 2027, and the studentship starts on 1 October 2027.
Funding details
Funded through the GW4 BioMed3 MRC Doctoral Landscape Programme. Covers UK tuition fees and a Doctoral Stipend matching the UK Research Council National Minimum (£21,805 p.a. for 2026/27, updated each year). Additional research training and support funding of up to £5,000 per annum is available.
What's required
Open to students from a variety of academic backgrounds. Applicants with mathematical or computational backgrounds should be willing to learn bioinformatics and laboratory work; applicants with biological or biomedical backgrounds should be willing to learn basic programming, data science, and machine learning. Significant reading/training in antimicrobial resistance, clinical mycology, and the diagnostic landscape is expected during the preparatory period.
How to apply
Check the GW4 BioMed website for the list of projects and application instructions. Select up to two projects and submit one application per candidate. Complete the online application form for an offer of funding by 5.00pm on 21 October 2026, then make an offer-to-study application to the chosen institution if shortlisted.
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