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Location/campus: White City Campus - Hybrid About the role We are aiming to develop novel geospatial modelling approaches to analyse trends in the genetics of malaria transmitting mosquito
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, better urban planning and use of space, and more recently for contact tracing and social distancing purposes. Explainable AI (XAI) for geospatial data modelling Machine learning and artificial intelligence
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, influencing and management leading an interdisciplinary academic team across Mathematics and Geospatial Science to deliver excellence across research and education activities. The appointee will work in
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requirements: You should be enthusiastic and self-motivated with a first-class/high 2:1 degree in a relevant engineering or physical science discipline (e.g., geophysics, earth science, geospatial
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inference, geospatial analytics, and dynamical modelling — with a growing emphasis on adapting tools for new geographies and near-elimination contexts. It offers the opportunity to contribute to high-impact
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that are embedded into routine health systems and data dashboards used to guide policy decisions. This role sits at the intersection of generative machine learning, statistical inference, geospatial analytics, and
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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(sedimentation, meltwater flows, vegetation changes, landslides). Process and analyse geospatial datasets, including 4D point clouds from UAVs and TLS, integrating them into adaptive design frameworks. Develop
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Computational Design advances generative and immersive design methods by integrating geospatial intelligence to address sustainability challenges in urban and landscape systems. Her research group has
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currently exists to map and explain the diverse mechanisms of housing exclusion. Addressing this gap requires integrating geospatial analysis, explainable AI (XAI), and behavioural research methods, including