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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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effort between School of Engineering and School of Chemical Engineering at Aalto University supported by our industrial partners. The PhD student to be jointly supervised by two supervisors; Prof. Hamid
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start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical Engineering), Richard Johnston (Materials) and Iain Whitaker (Medicine) Aligned programme of study: PhD
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health. There is likely a gendered dimension to this topic, given that predominantly women are victims of domestic violence. This PhD project will examine the relationship between climate-induced
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Project Overview The University of Sheffield, funded by the EPSRC and in collaboration with Shell, is offering a fully funded 4-year PhD studentship through the EPSRC Industrial Doctorate Landscape
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Qualification Type: PhD Location: Nottingham Funding For: UK Students Funding amount: Full tuition fee waiver pa (Home Students only) and stipend at above UKRI rates pa (currently at £20,780
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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to accommodate their own particular input setup and deciding the best modelling practice. This PhD project will aim at automatic solution development, supporting flexible input setups and addressing in one
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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