500 machine-learning-and-image-processing-"RMIT-University" Postdoctoral positions in United Kingdom
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Applications are invited for a Postdoctoral Research Assistant in Data processing for the MIGHTEE survey. This is a senior role funded through the UKRI Frontier Research Grant of Prof. Matthew
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developing and applying deep learning models, particularly in areas such as natural language processing (e.g. use of LLMs), computer vision (e.g. CNNs for image classification), and multimodal data integration
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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learning approaches to predict long-term treatment outcome from imaging and electrical data on clinical timescales, using a virtual cohort as additional training data. The candidate will also develop novel
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learning approaches to predict long-term treatment outcome from imaging and electrical data on clinical timescales, using a virtual cohort as additional training data. The candidate will also develop novel
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to