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Students Dr K Christofidou Application Deadline: 15 July 2024 Details Please note: This project is supervised by Dr Nick Warren, who is currently at the University of Leeds, but is moving to the Depaterment
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of rapidly responding to emerging health challenges. In this EPSRC funded project, we will combine expertise across the Universities of Leeds (Dr Adam Clayton, Prof. Richard Bourne), Liverpool (Prof. Anna
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, Machine Learning, Software Engineering, Chemical Engineering, Civil Engineering, Mechanical Engineering, Robotics, Geotechnology, Operational Research, Computational Physics
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, this project with apply the result to further train neural network-based machine learning models, with the aim of developing predictive tools for the rational design of future materials. Please state your entry
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research-intensive Russell Group University? Can you apply your expertise to support and complement the School’s existing strengths in digital design? The University of Leeds is one of the top 75
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Bachelor’s Degree in an appropriate field will also be considered. Subject Area Analytical Chemistry, Physical Chemistry, Machine Learning, Mechanical Engineering, Chemical Engineering, Materials Science
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? Are you looking for a new and exciting challenge to develop innovative digital tools combining CFD and machine learning to reduce manufacturing-induced deficiencies of ceramics? We have a vacancy for an
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Russell Group University? Can you apply your expertise to support and complement the School’s existing strengths in digital design? The University of Leeds is one of the top 75 universities in the world
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. This project aims to develop machine learning models to predict a particle shape and size for a given chemical formulae and crystallisation method. Extractive Language learning models developed will be able
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@leeds.ac.uk Project summary Ligand/material discovery has been carried out through laborious trial-and-error approaches. Recent advances in high throughput computational chemistry and AI/Machine Learning