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. Project description Data-driven mathematical and statistical models are increasingly used in life science research and healthcare. Quantifying the uncertainty associated with these models is crucial
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to develop and utilize innovative, interpretable data-driven analysis methods to significantly advance our understanding of immune cell inter-relations within the cancer microenvironment. We will apply
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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