Senior Research Associate in AI for Environment and Health

This is an exciting opportunity for a Senior Research Associate (SRA) to join the School of Geographical Sciences, to develop AI-driven techniques for modelling the complex interactions between heat exposure and human mortality. The SRA will work with Dr Rui Zhu and Dr Eunice Lo on the project “AI for heat mortality: decoding climate and socio-economic nexus” for 18 months. They will develop and apply AI knowledge graphs techniques to consider a full range of socio-economic determinants of weather exposure and health outcomes. The SRA will join the Bristol Climate Dynamics Group, Bristol Research Initiative for the Dynamic Global Environment (BRIDGE) and Quantitative Spatial Science (QuSS) research group. This post is funded by the Faculty of Science and Engineering’s Strategic Research Accelerator scheme.

The successful candidate will have a strong interest in effectively utilising and developing AI methods to tackle real-world environmental challenges. We are particularly interested in researchers with a PhD or equivalent expertise in deep learning methods (e.g. convolution neural networks, diffusion models, graph neural networks), foundation models (e.g. large language models), and/or knowledge graphs techniques (e.g. ontology engineering, knowledge graph embedding). The candidate should also have experience or an interest in applying these methods into addressing real-world issues such as climate change, public health, or social inequality.

Supervised by Dr Zhu and Dr Lo, the successful candidate will develop spatially explicit machine learning frameworks and interdisciplinary knowledge graphs to integrate high-resolution temperature, humidity, air pollution, mortality, demographic, socio-economic, urbanisation, housing, transport, greenspace, and access to healthcare data in the UK. This AI-powered integration will enable us to build a model to predict heat-related mortality, and to downscale this model to ultra-high spatial resolution for heat adaptation and urban planning.

Additionally, the post-holder will be responsible for

• Leading and contributing to academic journal articles
• Organising AI for the Environment workshops with collaborators and stakeholders
• Creating data products and novel AI-driven computational methods that enable the broader community to access and analyse interdisciplinary environmental and social data effectively

The project offers abundant opportunities for the successful candidate to disseminate project outputs to diverse communities (e.g., in academic conferences, government stakeholder workshops) and actively shape our planned impact-driven activities.

You should apply if

• Interest in Impact: You are motivated by the potential to create impactful solutions for environmental and social issues using AI.
• Expertise in AI Methods: You have a strong background in AI methodologies, particularly in deep learning, foundation models, or knowledge graph techniques.
• Practical Experience: You have hands-on experience applying AI techniques to address real-world challenges, particularly in areas such as climate change, public health, or social inequality.
• Interdisciplinary Collaboration: You thrive in collaborative environments and are eager to engage with a diverse team of researchers from various fields.

For informal queries, please contact: Rui Zhu, Senior Lecturer, rui.zhu@bristol.ac.uk

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