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Field
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reliable transmission of demanding multi-modal data such as haptic feedback, video, and 3D sensing data. This project will develop AI-driven predictive network intelligence to anticipate delay and network
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PhD MSCA - Acoustic and Ultrasound-based Predictive Maintenance Systems for Industrial Equipment Power converters are essential in numerous applications such as industry, photovoltaic systems
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Predicting infiltrative glioblastoma progression using advanced magnetic resonance imaging methods Project Supervisors: Michael Chappell, Steffi Thust Project Overview Glioblastoma (GBM) is the most
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
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research into predictive failure analysis methodologies for HVDC interconnection systems. This will include assessments of primary components such as switchgear and power transformers, as well as essential
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(FDD), and predictive maintenance for industrial systems. The position forms part of the EU-funded FLARE project, which addresses digitalisation, flexibility, resilience, and sustainability in industrial
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Primary supervisor - k.mares@uea.ac.uk Background: Falls are common in older people (there are around 3.4 million people in the UK over the age of 65 and 1 in 3 people within this age range will experience a fall). Falls incidence is a significant public health risk leading to injury and...
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the challenge of forever chemicals in drinking water. The aim of this research is to develop a smart data predictive model that will support utilities’ evidence-based decision-making to improve the resilience and
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10 Feb 2026 Job Information Organisation/Company Institute of Inorganic Chemistry, SAS Department Department of Theoretical Chemistry Research Field Chemistry » Computational chemistry Physics » Chemical physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application...
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, with direct industrial relevance to consumer product formulation and process optimization. This project aims to enhance the accuracy of surfactant behaviour predictions by integrating molecular dynamics