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and experienced Research Fellow in Computational Biostatistics with excellent technical skill and extensive experience analysing complex data sets in a translational research environment. You will apply
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the multimodal nature of cancer data. This includes data heterogeneity and hidden correlation structures, and their impact on learning performance. Implement and extend privacy-preserving techniques, particularly
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academic research group focusing on Contextual Artificial Intelligence for Computer Assisted Interventions. Our engineering research aims at improving surgical and interventional sciences by exploiting
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candidates will join the clinical study team to help curate high-quality data. The postholders will help support data analysis tasks and work on computational algorithms to help streamline data annotation
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component both for AI-driven modelling and predictions, and for bioinformatics analyses of wet-lab data. This will be performed by an excellent team of computational biologists with whom we have a long
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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engineering and physics laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About The Role We are seeking a highly motivated Research
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this project, using the chick embryo model, will create experimental situations in which cells of the limb bud are exposed to low, intermediate, or high physiological levels of the morphogen, SHH, and we will
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, state-of-the-art laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About the role We are looking for a highly motivated