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highly motivated to impact patient outcomes through translational approaches to the treatment of T cell malignancies. Experience with in vivo mouse immunotherapy models, protein/antibody engineering and
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complex algorithms and predictive models and determine analytical approaches and modeling techniques to evaluate potential future outcomes. Establish analytical rigor and statistical methods to analyze
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: We would like to recruit a postdoctoral fellow in cancer outcomes research, with a particular interest in decision/simulation modeling and cost-effectiveness analysis. The ideal candidate will have
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of mutational processes in human health and disease. We are an interdisciplinary team of experimental, computational, and clinician scientists allowing us to generate and analyse complex data from emerging
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. Studies incorporate approaches in both primary human immune cells and in vivo mouse intestinal model systems. Education and experience: Candidates must have a PhD or equivalent degree with a strong
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residues in their catalytic sites responsible for dephosphorylation. We have identified allosteric inhibitors for MKP5 and determined their structure in complex with these inhibitors. The goal is to
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research, with a particular interest in decision/simulation modeling and cost-effectiveness analysis. The ideal candidate will have strong quantitative skills and an interest in applying modeling
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single-cell or spatially resolved genomics methods Testing therapeutic interventions in models of ovarian and cardiovascular aging Designing in vivo lineage-tracing and labeling strategies paired with high
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the Pytorch library and running deep learning models. The successful candidate will work closely with a team of researchers and faculty members in the ClinicalNLP lab led by Dr. Hua Xu. More information of the
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positions) in the areas of privacy-preserving health data sharing, AI modeling and evaluation of medical and biological applications. The Postdoctoral Associate will be responsible for co-developing and