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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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, balancing efficiency and sustainability in AI deployment poses a significant challenge, calling for advances in model design and training to reduce environmental impact while maintaining high performance
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Department: Earth and Environmental Sciences Title: Quantifying Raindrop-Freezing Fragmentation Using a Cloud Chamber and Numerical Modelling Application deadline: All year round Research theme
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manufacturing methods and environmental storage conditions on the material properties and performance over time. The aim of this project is to understand how the properties of polyolefins (such as polyethylene
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Computational Chemistry methods to model enzymes and polymers. Designing and optimising novel biodegradable polymers. Integrating novel AI tools into the discovery process for new polymer candidates. Project
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on modelling and testing of new reactors with a view to optimising the best systems for mixing supercritical water (>378o C and 221 bar) with wastewater feed streams. This needs to generate residence times
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fees will be paid. The transition to a circular economy requires innovative solutions to improve the quality and consistency of recycled plastics, which are vital for reducing waste and environmental
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Project details: Noise pollution is a growing environmental issue and has become the second-largest environmental cause of health problems in Europe, just after air pollution. Among
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into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus on modelling and testing of new reactors with a view to optimising the best systems for mixing
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facilities, including advanced microscopy, controlled environment growth rooms, genomics, proteomics, and metabolomics platforms. • Opportunities to work across model and crop species, including Arabidopsis