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) in an appropriate discipline. Subject Area Computer Science & IT, Electrical & Electronic Keywords Artificial intelligence, floating-point arithmetic, numerical analysis, computer arithmetic, machine
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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to float over floodwaters. Recent work in behavioural biology emphasises how differences among individuals within groups (e.g. biomechanics, physiology, behaviour, cognition) determine group structure and
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an Ahmed body will be used as the baseline. Numerical studies will be performed using commercial CFD software. A correlation between experimental and numerical data will be determined. This project
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fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme! How does it work? Candidates will study for a four year, full time funded PhD
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part of the Sports Technology Institute with a long history of successful research collaborations with global companies and Loughborough University is currently ranked the best university in the world
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Funding for: UK Students Discipline: Engineering & Technology, Electrical and Electronic Engineering, Other Engineering, Physical & Environmental Sciences Qualification: Doctor of Philosophy in
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The project: For more than a decade, the University of Bristol has been at the cutting edge of bicycle driveline testing technology. We have partnered with Team GB for the last three summer Olympic
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour