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experience in Acoustics, Mechanical Engineering, Physics, Signal Processing or a closely related discipline. Strong practical experience in experimental acoustics/instrumentation (sensor selection, data
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will lead the natural language processing and language modelling aspects of the project, focusing on how sensor-derived motion data (from radar) can be transformed into linguistically meaningful BSL
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for impercepTible humAn INterfaces. SUSTAIN will tackle fundamental challenges across electronic textile-based sensing, wireless, electrochemical and design technologies with a focus on sustainable developments
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for impercepTible humAn INterfaces. SUSTAIN will tackle fundamental challenges across electronic textile-based sensing, wireless, electrochemical and design technologies with a focus on sustainable developments
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skills and ability to work across disciplinary boundaries. Desirable: Experience with image-based modelling workflows (CT/XCT segmentation-to-mesh pipelines). Experience with inverse problems, uncertainty
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and growing Department with a concentration of scholars researching related themes in the Public Opinion Research Network and the Gender and Inequalities Centre. To be successful you will have completed
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to net‑zero carbon emissions. The project examines how future technologies, propulsion concepts, fuels, operational changes and behavioural shifts can together deliver more sustainable aviation. In
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the neural-network control of a tiled array of fibre lasers in a coherent beam combination architecture, for unlocking novel scaling and beam shaping capabilities in real-time. You will work at the
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for spatiotemporal data (e.g., CNNs, LSTMs, Transformers, or Graph Neural Networks). Hybrid modeling: Experience with physics-informed machine learning or the integration of ML with data assimilation/multivariate
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warm and recover in a net-zero future. As part of this project, you will (i) quantify global and regional patterns of asymmetric climate recovery using CMIP6 Ramp-Up–Ramp-Down and Zero-Emission