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and Edinburgh Universities, and led by UCL. The SOFAIR Lab will pursue fundamentally new AI architectures, moving beyond incremental refinement of existing models. By advancing open, distributed, and
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for architecting, building and scaling UCL’s enterprise data platform. This includes modern data engineering, cloud data lakehouse development, distributed compute, data modelling, metadata/lineage services, self
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of the interactions between building stocks, heat and cooling demand, and electricity distribution networks. They will develop new computational approaches, contribute to the expansion of existing modelling tools, and
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computational modelling of magnetic field distributions and sensor performance, materials and device engineering (spin defect characterisation, optically detected magnetic resonance (ODMR), sensor packaging and
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Improving the clinical success of porous orthopaedic designs – experimental and finite element study
in stress distribution within the bone is vital to inform implant design. The purpose of this PhD is to investigate key parameters of porous implants to improve bone ingrowth. The student will develop
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distributed lag models. Findings from this project will inform clinical risk stratification, public health preparedness, and climate adaptation strategies, helping to protect vulnerable populations as climate
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capitalism Socio-environmental conflict Political Theory Climate change ethics Distributive justice Egalitarianism History of political economy History of political thought Liberal and conservative political
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distribution of microplastics Ecological restoration Community land ownership Upland management Sustainable rural tourism Resilience of coastal and deltaic social-ecological systems Water pollution and risks
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and Engineering A variety of approaches are used, including collection of experimental and observational data, epidemiological, mathematical, computational and statistical modelling, bioinformatics
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the project to have well-distributed data both in space and time. This will ultimately lead to higher quality (more spatially and temporally accurate, complete, precise) 3D models. However due to the complexity