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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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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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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
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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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data assembly, software interfacing, test design, statistical analysis, and results reporting. The role will also involve planning and managing project activities, building research skills and networks
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network with data from existing permanent seismic networks in Greece. Data processing will include implementation of automated detection of seismicity and subsequent derivation of a high-quality seismicity
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laser’, through 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
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the project. The researcher will combine seismicity data collected by a new onshore-offshore temporary seismic network with data from existing permanent seismic networks in Greece. Data processing will include
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of their mental models into a machine learning model, using dynamic Bayesian networks to understand, propagate and reduce uncertainty in their assessments. The research will apply models of distributed situation