Postdoc – Real-time detection of bioaerosols using novel instrumentation – Fungal spores
Met Éireann, Dublin, Ireland
Closing date: 14 March 2025
The successful candidate will work as part of an interdisciplinary team extending across multiple divisions within Met Éireann (Observations; Research and Applications; and Forecasting) and with partners in Dublin City University to complete the project objectives. The primary role of the Postdoctoral Researcher is to extend the current monitoring efforts to incorporate the detection and identification of fungal spores of interest.
Initially the Postdoctoral Researcher will be brought up to speed on the current methods used in training the Poleno devices and begin the process of adapting and translating this methodology for fungal spore. Target spore types will be identified and sourced for method development and training dataset generation. The processed training datasets will be used to develop classification algorithms, in conjunction with Swisens, to identify different fungal spores in near-real-time. This will be compared and evaluated to the traditional volumetric-microscopic Hirst method. This will require the Researcher to conduct the manual microscopic identification of fungal spores.
Typically, the development of aeroallergen networks is primarily centred around areas of population density. However, the inclusion of potential plant-pathogenic bioaerosol, such as certain fungal spore types, offers additional benefits to agricultural sectors. Therefore, the Postdoctoral Researcher will statistically evaluate the suitability and spatial coverage of current sampling sites with regards to both population density and potential agricultural applications being cognisant of guidance and best practice from EUMETNET AutoPollen, EAN and EAS. The finding of this analysis will be used to guide the selection of future Poleno sites. This work will also involve participating in working groups focused on QC and siting as part of the EUMETNET AutoPollen project.