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such as UK Biobank. You will design and optimise scalable computational pipelines and algorithms to construct and evaluate foundation models for whole-body and abdominal MRI. Alongside this, you will
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classification algorithms including machine learning); and the output data and interpretability. The project “SORS in the community” is funded by the EPSRC (https://www.ukri.org/news/new-tools-aim-to-improve-early
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pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in Latin, contributing to the creation of a 100-million-token annotated corpus
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modelling are essential. Experience with healthcare data, algorithmic fairness, or deep learning for biomedical data will be advantageous. The successful candidate will contribute to high-impact publications
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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, which involves building a large corpus of Latin texts (data collection and pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in
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and implementing vision processing algorithms that enable robust robot tracking and autonomy. The ideal candidate will possess hands-on experience designing, implementing, and deploying computer vision
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Edinburgh based team of Sandy Hetherington to lead efforts to quantitively characterise key morphological characteristics of fossil plants and assemble data on their ecology and global distribution
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gene gain/loss events, horizontal gene transfer, and functional diversification within gene families. You will apply statistical models and machine learning algorithms to identify associations between