We are now looking for two postdoctoral researchers to support our research in the NatalieProject & UrbaQuantum projects! NatalieProject The successful applicant will contribute to the NatalieProject by developing AIalgorithms that integrate data from various sources to identify patterns and correlations between variables and enhance the understanding the impact of spatiotemporal variables in climatic events. The algorithms will further assess the environmental attributes to identify feasible naturebasedsolutions (NBS) and evaluate their performances to provide decision support. The successful applicant will focus on applying machinelearning technologies to establish a smalldata approach to ensure data quality and trustworthy for the elaboration and application of data-driven and AI algorithms. This data contextualisation will enable to apply explainable AI to understand physical interrelation and connections between regional impacts and the implementation of the NBS. Details & Application: https://jobs.exeter.ac.uk/hrpr_webrecruitment/wrd/run/etrec179gf.open?WVID=171839ediw&LANG=USA&VACANCY_ID=831982sPkU UrbaQuantum The successful applicant will contribute to the project UrbaQuantum to develop hydraulic and waterquality modelling approaches to analyse the flow interactions between sewer discharge of surface runoff, as well as the dynamics of pollutants and pathogen propagations associated with water movements. The successful applicant will focus on expanding the capacity of the Centre for Water Systems’ existing methodologies and models to simulate urbanrunoff dynamic and waterquality, analyse the propagations of flows, pollutants and pathogens within urban environment. The post will also combine hydroinformatics analysis techniques and realtime monitoring data from various sources to predict the performance of sewer network and overflows to support effectivemanagement, and develop strategies to control pollutions at sources. Details & Application: https://jobs.exeter.ac.uk/hrpr_webrecruitment/wrd/run/etrec179gf.open?WVID=171839ediw&LANG=USA&VACANCY_ID=712548sPkU Apply by //