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SURGERY (06740A) Is this split and/or fully grant funded? Yes Duties and Responsibilities A postdoc position is available in Dr. Gahtan’s lab at the Burn and Shock Trauma Research Institute in the Stritch
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory Science – Leveraging drug development and regulatory
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fellow will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. UiO
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converting complex technical concepts—often spanning computational biology, AI/Machine Learning-enabled discovery, experimental workflows, and translational programs—into clear, accurate visuals and narrative
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of novel computational/biostatistical/machine learning methods for the integration of multiple, diverse dataset and the synthesis of hypotheses around the molecular mechanisms that drive the co-occurring
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postdoc with interests in RNA virology and host-pathogen interactions. For detailed information about the laboratory’s research, see our website (http://www.mouncelab.com). Experience in molecular virology
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Trustworthy AI Systems NSF Research Traineeship , the Digital Trade and Data Governance Hub , the Center for Machine Learning, and the Human-Computer Interaction Lab at UMD, and the Center for Equitable AI and
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of different concepts. This endeavour is typically accompanied by new insights and synergetic effects due to the inherently different viewpoints of the previously separate fields. Our task force on machine
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models motivated by biological and therapeutic applications are particularly encouraged to apply. Expertise in statistical or machine-learning methods is also welcome, as connection with experimental and
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and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR