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Clinical application of machine learning algorithms to determine appropriate antibiotic use in children with Gram-negative bacteria infections

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  • Full or part time
    Dr Y Hsia
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Digital health is a growing and productive field in recent years. The application of machine learning (ML) techniques in electronic healthcare databases has been successfully used for clinical diagnosis, outcome prediction, and disease progression. With increasing global antimicrobial resistance (AMR), appropriate antibiotic selection plays a key role to tackle AMR. The overall aim of this project is to develop and apply ML algorithms using global antimicrobial resistance data, to determine appropriate antibiotic use for children.

Funding Notes

Applicants should have a 1st or 2.1 honours degree (or equivalent) in a relevant subject. Relevant subjects include Pharmacy, Molecular Biology, Pharmaceutical Sciences, Biochemistry, Biological/Biomedical Sciences, Chemistry, Engineering, Statistics, Computer Science or a closely related discipline. Students who have a 2.2 honours degree and a Master’s degree may also be considered, but the School reserves the right to shortlist for interview only those applicants who have demonstrated high academic attainment to date



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