65 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Newcastle University
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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PhD studentship in Mechanical: Bioprinted 3D In Vitro Cardiac Models Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional
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the programme code: 8030F · select ‘PhD Chemical Engineering (full time) as the programme of study You will then need to provide the following information in the ‘Further Details’ section: · a
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the most energy‐intensive infrastructures in modern economies, with their demand projected to rise sharply as digitalisation, artificial intelligence (AI), and cloud computing expand. This growth presents
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8090F select ‘‘PhD Mechanical Engineering (full time) - 8090' as the programme of study You will then
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of OI fractures and its management. The successful candidate will have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing
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registered select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8060F. select ‘PhD Electrical and
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on more than bone growth; it depends on a complex dialogue between immune and skeletal cells. When this communication falters, healing slows or fails. This PhD will explore how mechanical and topographical cues
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability