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Field
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) and the University of Warwick seeks to develop flexible digital twin models that will enable novel, integrated solutions to the decarbonisation of heating and cooling on large industrial and commercial
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gender inequality impact mental health during the teenage years and early adulthood. The project consists of three work packages (WPs): • WP1 and WP3 will generate novel data in new school-based
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work with large-scale behavioural data sets using a range of approaches, including heritability analyses and machine learning. Some data for the project already exist, but additional data will be
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problems to help pave the way for a sustainable and healthy future. From forest fires to big data, from obesity to malnutrition, and from molecules to the moon: we cover the full spectrum of the natural
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problems to help pave the way for a sustainable and healthy future. From forest fires to big data, from obesity to malnutrition, and from molecules to the moon: we cover the full spectrum of the natural
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to generate the next generation of extremely sensitive inertial sensors for application in big-science projects and high-tech industry where there is an urgent need for improved active vibration isolation while
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large language models (LLMs)—that is, the inability of a model to effectively process or understand visual information. This work involves integrating visual encoders with language models to create
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (http
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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materials. The ability of their subcomponents to undergo large amplitude displacement, such as macrocycle shuttling in a rotaxane, make them ideal structures for mechanical coupling. We are currently