Fungal pathogens within the Candida genus, including C. albicans, C. parapsilosis and C. auris, represent a growing public health concern on a global scale. Resistance to key antifungal drugs, particularly azoles and echinocandins, is on the rise. Increased virulence or resistance is driven by multiple factors including the dual use of antifungals, but our understanding of these drivers is incomplete. The implementation and utility of genomics in Candida epidemiology significantly lags behind its use for bacterial pathogens, and there is little data on the transmission dynamics of these species between clinical and non-clinical (One Health) environments. This PhD project will combine existing genomic data with novel omics and metagenome data from clinical and non-clinical settings. It will also characterise extensive wastewater and environmental samples from the UK and the Netherlands.
The position is based at the UMC Utrecht where the bioinformatics part of the project will be carried out, and at the Radboud UMC Nijmegen where the laboratory work will take place. The successful candidate will generate sequencing data from existing collections and prospective and environmental sampling. The candidate will apply bioinformatics techniques to establish and expand whole genome sequencing databases, contribute to transmission and co-occurrence analysis and validates and characterises new markers. Furthermore, the candidate will analyse environmental metagenomics data for occurrence of Candida strains. This PhD position is part of the JPI-AMR project
Fugaci and a collaboration between the UMC Utrecht, the Radboud UMC Nijmegen and several renowned international partners.
The candidate will carry out sampling and sequencing, will analyze data, will present the research and write open access scientific publications and will collaborate with other researchers within Fugaci.