29 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions at Nature Careers in United States
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Job Description SJCRH Position Overview: The Department of Information Services is seeking a highly skilled and motivated faculty- level Clinical Informatics Researcher to join our dynamic clinical
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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international conferences. Required Qualifications* PhD in computational biology, bioinformatics, data science, or a related quantitative field. Proficiency in Python and/or R; experience with high-performance
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Company Information: A full-time postdoctoral fellow position is available in Professor Wenyi Wang's lab at the Department of Bioinformatics and Computational Biology, the University of Texas MD
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SJCRH Position Overview: The Department of Information Services is seeking a highly skilled and motivated faculty- level Clinical Informatics Researcher to join our dynamic clinical informatics and
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bioinformatics, computational biology, genomics, statistical genetics, or a related quantitative field, together with demonstrated expertise in large-scale genomic data analysis and significant experience in
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collaborative research environment that brings together computational scientists, clinicians, and biomedical researchers to address pressing challenges in precision medicine and biomedical data science. QBRC is a
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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neuroscience, or computational neuroscience. The postdocs would be part of a multidisciplinary neural engineering and behavioral neuroscience team to study neural mechanisms of drug self-administration and
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-derived organoids and assembloids, engineered ECM environments, and in vivo mouse models, working in close partnership with the lab's computational team to generate data-rich spatial multi-omics datasets