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Postdoctoral position in AI for protein design with applications to TCR & BCR models The lab of Prof. María Rodríguez Martínez at the Department of Biomedical Informatics & Data Science, Yale School
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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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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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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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. 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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from clinical research to molecular studies in mouse models of disease. Training/Mentoring: The postdoctoral associate will have the opportunity to gain experience with in clinical and basic research
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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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/CT and PET/MR imaging for cardiac applications. Responsibilities involve working with preclinical large animal models, preclinical and clinical PET imaging, image analysis, kinetic modeling, data
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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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a particular focus on cytokine-based drugs, using immune competent murine models and human cell culture systems for early drug development. We also study mechanisms and determinants of immune related