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include designing and executing experiments to interrogate host-microbe interactions, analyzing and interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical
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developing this program. We are also particularly interested in strengthening the group working the CMS Track Trigger or Forward Pixel Detector for the HL-LHC upgrades. A PhD in experimental high energy
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Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms) as part of the CTECH Postdoctoral Fellows program. This
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interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical approaches to characterize microbial community structure and function, working with graduate students
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complementary expertise spanning engineering student learning and identity, faculty development and pedagogy, design- and project-based learning environments, institutional transformation in engineering education
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Postdoctoral Associate to lead a multidisciplinary project focused on two primary tasks: Developing a simplified version of the Cornell Net Carbohydrate and Protein System that can use feed ingredients
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, computational methods and theories for humanistic and social scientific inquiry, and the ethical, political, or historic dimensions of artificial intelligence but we will consider outstanding applicants working
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analysis and manuscript preparation, with opportunities to publish as first author as well as collaborate on papers with faculty and students. This role provides an excellent opportunity to develop expertise
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expertise spanning engineering student learning and identity, faculty development and pedagogy, design- and project-based learning environments, institutional transformation in engineering education, and
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international team of experts Assisting with project coordination and management Developing multiple peer-reviewed manuscripts as a lead-author and a co-author Requirements: PhD in ecology, disease ecology