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tackling the above challenges with novel system designs and tailored AI/ML based methods. Candidate’s profile A First Class Bachelors degree and/or Masters degree in a relevant subject (computer
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LevelBachelor Degree or equivalent LanguagesENGLISHLevelExcellent Additional Information Eligibility criteria Mobility rule - Applicants cannot have resided or carried out his/her main activity - work, studies
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performed annually in the UK. However, about 20% require revision within 15 years due to complications like implant loosening, dislocation, and fractures caused by suboptimal implant positioning. With primary
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About the Project Main description: Fiber-polymer composites are innovative ad sustainable alternative in construction due to their lightweight, excellent fatigue and durability, which are widely
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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be based in the Primary Care research group in the Division of Population Health as part of a cross- institution multidisciplinary team co-led by Professor James Catto (University of Sheffield) and
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will