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A PhD opportunity at the EPSRC Centre for Doctoral Training in Quantum Information Science and Technologies at the University of Sussex School of Mathematical & Physical Sciences The University
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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hypothesis of the proposed research is by use of intelligent and integrated control of the input power electronics, fluid handling, and thermal control in a holistic approach, current efficiency and lifespan
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
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include: Developing innovative serration and permeable surface designs to further reduce trailing edge noise. Conducting detailed fluid dynamics, aerodynamics, and aeroacoustics investigations to understand
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: Dr James Yates, Director GSK Aligned programme of study: PhD in Mathematics Mode of study: Full-Time Project description: HIV remains one of the most persistent and challenging infections to cure due
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects