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of intensified NbS strategies. Applicants should have a minimum equivalent to a UK upper second class degree (2.1) and preferably an MSc in a relevant subject such as Environmental Engineering, Environmental
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environmental inputs, algae physiological parameters and microbial community eDNA data to develop predictive mechanistic models which can be utilised to develop an optimal cultivation strategy. The project is
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Fully funded positions available to start in 2025 or early 2026 Projects span plant genetics, climate-resilient breeding, AI and data science, soil health, sustainable agriculture, circular economy
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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, reliability, and environmental resilience. The proliferation of intelligent systems has led to increased energy consumption, raising concerns about sustainability and operational costs. Energy-efficient
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immobilisation, or even the chemical-physical environments thought to underpin the origin of life. This project offers a unique opportunity to work at the interface of experimental physics, data science, and
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, environmental data science, or a closely related STEM discipline Demonstrated expertise in urban spatial data analytics, with proficiency in GIS software (e.g. QGIS, ArcGIS) and geospatial methods Experience in
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studentship is closely related to the current cohort of MOAP-PhD students and the wider PhD cohort in the group of meteorology and climate and the School of Geography, Earth, and Environmental Sciences
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of environmental economics and innovation. The successful candidate will play an integral role in supporting data-driven, policy-relevant research examining the intersection of environmental challenges and
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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives Understanding