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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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experimentation and finite-element modelling. Research themes would be flexible including green steel formability under the EPSRC ADAP‑EAF programme for automotive and packaging applications; or micromechanical
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, which will be used to implement high frequency and high efficiency IVRs for HPC applications. Objectives:-Fabrication, characterization and modeling of the composite magnetic materials.-Modeling
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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layers, thorough FLA processing, and extensive materials characteri-zation using XRD, electron microscopies, TOF-SIMS, electrochemical methods, etc. Modeling and simulations should help us to explain
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cells or the tumor microenvironment reduces tumor growth and extends survival in preclinical models, underscoring their potential as dual-function therapeutic targets. To address this, we aim to develop
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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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response timelines. Building on this foundation, the project will apply scenario modelling and simulation techniques to investigate emergency event propagation, routing strategies, vehicle-task assignment
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Researcher in Language Evolution / Probabilistic or Evolutionary Modeling / Primate Communication (m/f/d, E13 TV-L, 75%) The position will be filled for a fixed term until June 2029. Payment is at 75