998 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" Fellowship research jobs in United States
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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and
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of next-generation communication infrastructures. Qualifications: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer Science, Industrial Engineering, or a closely related field
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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune microenvironment architecture. Collaborate with wet lab
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selection programs. Learning Objectives: By the end of this training/research experience, the fellow will be able to: Explain the structure and functional organization of the bovine genome and describe how
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of childhood allergic diseases. The candidate will develop machine learning–based biomarker prediction models to identify microbiome-derived signatures associated with allergy risk and immune tolerance outcomes
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of research, testing and data collection, analysis and evaluation, and writing reports which contain descriptive, analytical and evaluative content. The purpose of this role is to acquire the professional
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic
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uses cryo-electron microscopy to understand how viral proteins are recognized by antibodies at an atomic level, and how that recognition can be exploited to design effective vaccines. You will learn