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within materials science and engineering. Use cases will be defined within different manufacturing techniques of lightweight structures to enable novel development of materials and process design. The PhD
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education in digitalization and electrification including renewable energy sources, electric vehicles, industrial IoT, AI, 6G communication and wireless sensor networks as well as research and education
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statistical methods for genetic and genomic data analysis; proven ability to build and maintain collaborative networks across academia, industry, and international partners; strong organizational skills and the
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the Collaborative Research Centre for Low Carbon Living. The project uses agent based modelling (ABM) to represent consumer behaviour, social networks and their responses to non-financial incentives and barriers in
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modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
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operation in hybrid quantum–classical networks across intra- and inter-domain settings. The candidate will study architectural models, including the placement and roles of quantum repeaters, memories, and
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Resilience Assurance for 5G/6G Networks Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The
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applying different multivariate calibration strategies and machine learning approaches. Finally, the variation of the sensor measurements will be studied in relation to the cow’s health and combined with
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The School of Computer Science and Electronic Engineering at the University of Essex hosts research in communications, networking, signal processing and optimisation. The post will be based within
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs