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seeking a postdoctoral researcher to investigate how the use of visualization and simulation tools impacts undergraduate students' understanding and attitudes in topics related to semiconductor physics
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postdoctoral fellow interested in gaining trainingand experience in disease modelling and translational science. The successful candidatewill lead collaborative efforts among basic and clinical researchers and
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inferential statistics, model testing, and power analysis Desired Qualifications Demonstrated mentoring and teaching ability in the areas of statistical methods and use research-related tools Experience with
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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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to research design, data collection, data analysis, modeling, simulation, visualization, and/or dissemination efforts. Collaborates with faculty, researchers, staff, and students from varied academic and
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high energy physics. We have a strong interest in combining physics knowledge with advanced machine learning techniques to accelerate research in beyond the standard model and dark matter physics
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the area of electric power grids. Essential Duties and Responsibilities: • Perform cyber-physical system modeling and simulation for the power grid. • Perform research on power system dynamics and
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collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex biomedical and social processes and systems
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of biological invasions by plants, insects, and tree pathogens in forests worldwide. FISC uses the “synthesis centre” model that has been successfully applied in various other socio-ecological synthesis centres
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accompanied by theoretical modelling and simulation activities, which will be in the responsibility of a postdoc also employed in the project. For more information about the project, please contact