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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
techniques and approaches to difference image analysis, survey-scale photometric calibration and detrending, periodicity searches, and/or other areas. A negotiable fraction of this role is reserved
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
techniques and approaches to difference image analysis, survey-scale photometric calibration and detrending, periodicity searches, and/or other areas. A negotiable fraction of this role is reserved
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funded by the European Commission as a Horizon Europe Research and Innovation Action (RIA), (HORIZON-HLTH-2021-TOOL-06). Genegut has 9 partners from 8 different European countries. The consortium includes
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making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in the world. Being a part of Durham is about
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employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video unable to load from YouTube. Accept
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) quantification tools, holding back early immunogenicity risk assessment in the context of protein drug development. A clearer understanding of the rules governing T cell activation would form a paradigm shift in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
Associate position involves laboratory research in biomedical science. The position studies focus on an animal model of arthritis and include in vivo studies (muscles and behavioral analyses, imaging
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paradigm shift in development of Biologics. A critical challenge preventing this is the current limiting volume of high quality and well-characterized in-vitro T cell immunogenicity data. In this project, we
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for such models include high-resolution 3D imaging, time-resolved materials characterization, and atomic structure determination. Scientific instrument data is often multimodal in nature and developing DL models
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-cell genomics, transcriptome imaging, optical electrophysiology, and machine learning to study how the genome builds a brain across spatial and temporal scales. Key questions we aim to address include: 1