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formulation. These models will enable rapid scenario testing, predictive analysis, and early decision-making, thereby reducing experimental workload and accelerating development timelines. Life cycle assessment
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of peatlands under future climate change, incorporating projected outcomes from restoration activities and the identification of environmental tipping points from mechanistic modelling of species distributions
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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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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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an independent impact assessment of potential climate interventions in the Arctic marine environment through laboratory experiments and computer modelling. The team will develop physical, climate and ecosystem
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environmental benefits, and enable smarter investments in water infrastructure and management. By joining this ambitious effort, you will contribute to improve the natural environment, the state of our rivers
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
biggest environmental challenges? This fully funded PhD offers a unique opportunity to develop energy-efficient, cost-effective, and carbon-reducing manufacturing processes — placing you at the forefront
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, and a strong interest in applying advanced physical and computational methods to real-world challenges in energy and environmental technologies. The research will focus on the nano-architecture
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, including remote sensing Expertise in cloud physics, preferably cirrus clouds Aircraft performance/emissions modelling preferred but not required Creative problem-solving skills and ability to work
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. Additionally, Life Cycle Assessment (LCA) and Environmentally Extended Multi-Regional Input-Output (EE-MRIO) models will be employed to calculate the carbon footprints of various low-carbon travel modes and