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Efficient coding in touch: Exploring cortical feature tuning in the somatosensory system through the lens of efficient coding School of Psychology PhD Research Project Self Funded Dr Hannes Saal
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specialized quantum error correction codes that maximise the quantum advantage attainable in the quantum estimation of classical fields, while also considering reasonable physical constraints that are imposed
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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instructions for maintenance works to be carried out in a timely, cost efficient manner by either University staff or external contractors, ensuring works comply with current legislation, Health & Safety codes
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to identify risks and plan alternative methods to meet project requirements Essential Application and interview Experience of python coding to support data analysis Desirable Application and interview Further
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Knowledge of the role and function of splicing and the non-coding genome Essential Application/Interview Experience with analysis of large ‘omics data sets in a research Essential Application/Interview
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-dimensional flame structure code, PREMIX. This will allow the development and validation of chemical kinetic models of these alternative fuels combustion. Funding Notes 1st or 2:1 degree in Engineering
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on an existing experiment design. This will allow the student to familiarise themselves with the relevant Physics, literature, Fortran code, Python analysis tools, and simulation setup while providing a valuable
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researchers from the Universities of Sheffield, Exeter, Cambridge, and Warwick. The code will be developed to ensure world-class physics capabilities, maintaining the UK’s solar physics community
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specialized quantum error correction codes that maximise the quantum advantage attainable in the quantum estimation of classical fields, while also considering reasonable physical constraints that are imposed