16 phd-position-in-data-modeling-"UCL"-"UCL" PhD positions at University of Sheffield
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About
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grade. Generate data through comprehensive laboratory grinding tests on various rail grades to train and validate the ML model. Utilise numerical modelling to establish acceptable thresholds for surface
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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PhD in Quantum Error Correction and its Applications School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Yingkai Ouyang, Dr P Kok Application Deadline: 15 January 2026
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PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering
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Exciting Fully Funded PhD Opportunity: Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies - Help Shape the Future of Clean Energy Storage! School of Mechanical, Aerospace and
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proposed supervisor(s). Information on what documents are required and a link to the application form can be found here - https://www.sheffield.ac.uk/postgraduate/phd/apply/applying The form has
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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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