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examines how administrative processes shape people’s experiences of accessing mental health services. The post-holder will lead key elements of a longitudinal qualitative study exploring how people navigate
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materials developed within the EXPRESS programme. You will design and implement fabrication process flows within a cleanroom environment, including thin film deposition, lithography, mask design and etching
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-quality, repeatable data. Develop and apply signal processing workflows for weak transient signals, long-term monitoring, feature extraction and statistical analysis. Support sound playback/stimulation
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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the assessment process and will play no role in the decision to appoint. The post is available from the 31st March 2026 and is offered on a full time (36.25 hours per week) fixed-term contract until the 31st
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and their experiences of education. The post offers an exciting opportunity to contribute to the final stages of large-scale project that aims to understand what processes are linked to the mental
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, computer simulations and machine-learning analyses. The University of Nottingham offers a wide range of employee benefits. More information can be found at: https://www.nottingham.ac.uk/hr/your-benefits/a-z
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individually, make a real difference. The role Applications are invited for a Research Fellow in the Energy and Materials research group in the School of Chemistry and Chemical and Process Engineering at
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hydrological models to improve malaria transmission estimates’ funded by the UKRI Natural Environment Research Council (NERC). The project aims to embed hydrological processes in models of malaria transmission
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model for storm surge prediction. Data Analysis: Process and analyze climate, ocean wave and coastal data to improve model accuracy. Research: Conduct research to enhance wave modelling techniques and