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18 Apr 2024 Job Information Organisation/Company The University of Manchester Department School of Engineering Research Field Engineering » Civil engineering Engineering » Geological engineering
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Applications are invited for a Research Assistant or Research Associate to work on efficient machine-learning systems for earth observation. The post holder will be part of the Computer Architecture
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the Universities of Manchester, Lancaster, Edinburgh, Cambridge, Bristol and Warwick on the Mathematical and Computational Foundations of AI. Machine learning (ML) and AI methods are becoming increasingly popular as
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to the long-term goal of nuclear decommissioning at RAICo1, Dalton Cumbria and The University of Manchester. During nuclear decommissioning, operators face severe risks from unknown environment to dealing with
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of Manchester from October 2024. The use of machine learning methods and molecular simulations for polymer design and property prediction is the new frontier in polymer science. This project aims at using a mix
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to enforce consistency with the resolved CFD (averaged to the systems code resolution). The identification of regions where the CFD grid is resolved can initially be done manually. With machine learning
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challenge hindering further progression is the lack of a high-throughput, automated, unbiased approach to analysing and characterising hydrides in 2D and 3D. The use of deep learning (DL) based algorithms
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. The candidates will also evaluate individualized interventions (e.g. machine learning-based speech enhancement algorithms, hearing aids). EASYLI consists of 5 academic partners and 4 non-academic
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 7 days ago
Job Offer PhD Studentship in Social Statistics in Digital and Computational Demography University of Manchester and Max Planck Institute for Demographic Research We are pleased to invite
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will research and develop machine learning-based technologies for acoustical scene analysis and improvement of the acoustical signal in the context of occupational communication in safety-critical