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to advanced diffraction methods. They will be expected to contribute to the development oof cutting-edge manufacturing solutions that have the potential to revolutionize industrial implementation in space and
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Deep learning methods for modelling of speech
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cutters and methods (assessed at: Application & Interview) Experience in offline programming of CNC machinery and the use of programme verification software (assessed at: Application & Interview) Experience
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characterisation equipment at the University of Sheffield. There may also be opportunities to learn and apply computational methods such as process simulation using Population Balance Modelling, DEM simulations and
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net zero. https://greenindustrialfutures.site.hw.ac.uk/the-programme/training-programme/ Project: The automotive industry faces significant challenges in reducing CO2 emissions during the painting
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line with project objectives. Plan and conduct ecological monitoring fieldwork in three English cities, utilising novel instrumentation and tried-and-tested sampling methods (vegetation, birds, insects
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numerous human activities, from fishing to climate change. Effective conservation and management of marine ecosystems requires that we understand the dynamics of marine biodiversity in both space and time
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bioclimatic data from >1000 Arabidopsis ecotypes. KEY METHODS AND SKILLS: Experimental Design and Execution of Experiments: You will learn to execute microcosm “common garden” experiments involving
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Computational photochemistry/Vibrational control in transition metal complexes School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application Deadline
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collaborative programme of research funded by the Aerospace Technology Institute (ATI) with several Industry partners, including Airbus, GKN and Renishaw. Critical for the implementation of additive manufacturing