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and led by Prof Graham Leggett. The aim of our five-year programme is to develop a new modular approach to the creation of photonic materials, inspired by structures found in biological photosynthetic
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and time-resolved spectroscopic studies on such systems using laser-based methods and characterizing reversible interactions between such complexes and biomolecules is desirable. You will be integrated
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PMLD. Design and implement online, asynchronous training materials. Contribute to data collection using quantitative and qualitative methods. Collate, input and organise data into data analysis software
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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media and society, or equivalent experience. Experience of delivering excellent, innovative courses involving the teaching of digital identities, social media cultures, digital activism, digital methods
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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Next Generation Aero-Engine Sealing Technologies
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experience of treatment. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies
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of Information, Journalism and Communication at the University of Sheffield is one of the major research and teaching establishments in the UK. We are committed to a research and teaching programme that takes
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PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios