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involve leveraging advanced natural language processing and medical image analysis to transform imaging data into clinically relevant information. Additionally, it will explore the use of multimodal fusion
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nature conservation priority. Dune slacks are seasonally flooded, and the extent, depth and duration of this flooding is a key control over their ecology. Understanding the dynamics of this flooding is
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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processes. Carbonate biomineralisation is a key process in global carbon cycling, but there are major gaps in our understanding of how biominerals form. We lack a quantitative understanding that can predict
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, natural language processing, and computer vision is advantageous. Proficiency in common machine learning frameworks (e.g., PyTorch, TensorFlow, MxNet, Huggingface-Transformer) is highly desirable. Not
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mother tongue is not English must meet any one or a combination of the following: A minimum IELTS average score of 6.5; with a minimum of 6.0 in each of the four components A master’s degree awarded in
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their property. Methodology: The aim is to apply a newly developed Coupled Human And Natural Systems (CHANS) model to simulate and understand the interactive human behaviours and social dynamics before and during
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and Mathematics Dr Hailey Austin, Lecturer in Games and Arts Dr Lynsay Shepherd, Reader in Cybersecurity and Human-Computer Interaction Dr George Lovell, Senior Lecturer in Psychology Entry Requirements
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Project title: Transforming Menopause Care through At-Home Hormone Monitoring Department/School: School of Psychology and Clinical Language Sciences Supervisors: Dr Katherine Finlay, Psychology