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computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET
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Position Summary The Turner Lab at WashU in St. Louis focuses on advancing the emerging field of Precision Genomics, which we define as “determining all possible relevant genomic variation within
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of pediatric cancer patients and discover the impact of therapeutic exposure on development of secondary neoplasms in adult survivors. Position Responsibilities: Evaluate bulk-tumor deconvolution algorithms
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
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of biomedical research. You will benefit from access to unique datasets and expertise, a top-ranked scientific environment, and superb benefits, mentoring, and professional development. St. Jude is seeking
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and
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on developing advanced new algorithms, testing and validation, and applications in medical neuroimaging and non-imaging modalities. The candidate will contribute to the overall research goals and objectives
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located at the MU Bond Life Sciences Center and focuses research on emerging and re-emerging infectious diseases, especially influenza viruses and SARS-COV-2, by developing and applying integrated, multi
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implementation of various projects, including (but not limited to) scaling, algorithm development, scaled score development and documentation. Support the creation, management, and retention of large-scale data