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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve
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of potential options for implementation. This will include prototyping and testing of various implementation options, analysis and documentation of results. Project 2 - Future Power System Modelling: As part of
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(https://www.bookbotkids.com/ ) is an AI-powered platform and app designed to enhance children’s reading engagement and fluency through interactive AI agents using advanced language models. About the
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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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models at many scales including electron dynamics, soft-matter physics, materials-biomolecules interaction and device physics exploiting the collaboration with a multidisciplinary team of theoreticians and
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models. TensorFlow or PyTorch is desirable. How to apply To apply, please ensure you have digital copies of the below information: • Curriculum vitae; encompassing any research presentations and/or
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. This position will focus on one key stream: understanding and improving the interaction between EVs and roadside barriers. This will involve: Modelling EV crash dynamics with conventional and SRB barriers
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palliative care models. It comprises a number of sub-projects including a systematic literature review, a synthesis of existing qualitative data, and the design and analysis of a quantitative preference survey
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of agricultural innovation, exploring how advanced weather forecasting, crop modelling, and digital decision tools can be harnessed to support smarter, more agile on-farm decisions. It offers a unique opportunity
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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method