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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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found on our web page, fds.yale.edu. Yale’s Data Science Initiative has supported the rapid growth of the departments of Statistics & Data Science and Computer Science, as well as many interdisciplinary
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(SUDs), psychiatric conditions, and other behavioral and lifestyle characteristics that impact human health using large datasets and biobanks including the Million Veteran Program (MVP), the SUD working
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, survey testing, data quality monitoring, and more. Conduct econometric analysis under the direction of senior researchers. Manage relationships with collaborating institutions, including data collection
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publishable manuscript; provide one lecture as part of the CEAS Postdoctoral Associates Lecture Series; and teach one undergraduate course. Application Instructions To apply, please submit cover letter, CV
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inflammation, multiparameter flow cytometry, and bioinformatics/computational biology is desired. Please send curriculum vitae, three names of reference and a one-page summary of research background and
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where it would be cost-effective to screen and (iii) incorporating multi-omics data to better identify at-risk individuals beyond lifestyle and environmental approaches alone. Our research program has
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. Qualifications We are seeking candidates who meet the following criteria: A PhD or equivalent degree, already obtained, in a related field e.g., philosophy, law, computer science, data science, social sciences
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Post-Doctoral Position in Deep Learning for MRI Reconstruction at Yale University Title: Postdoctoral Associate, Yale School of Medicine Department/Division: Radiology and Biomedical Imaging, Bioimaging Sciences Position Description: Join an exciting effort to develop a low-field, low-cost, MRI...
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School of Medicine. We develop and apply innovative experimental and computational approaches to study cellular heterogeneity and its impact on tissue function in health and disease. Our interdisciplinary