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Field
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visual representations that are most challenging for students, the misconceptions that persist across instructional contexts, and effective strategies for teaching visual literacy as a core scientific
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 12 days ago
initiative between two Inria research teams: Gamble (Inria Nancy) and Ouragan (Inria Paris), in collaboration with the ANR StratMesh project. The objective is to develop new methods and reliable visualization
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systems for visualization and analysis Technical knowledge of large, dynamical systems (preferability the atmosphere) Knowledge and experience in writing scientific code Skills in clear, concise writing
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microscopic traffic simulation and visual analytics platform for Traffic Impact Assessment (TIA). Duties and Responsibilities The appointees will conduct research and development in one or more of the following
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. This position is best suited to those who enjoy statistics, coding, manipulating and visualizing data, and other quantitative analysis tasks. Work Performed The new researcher will leverage knowledge and skills
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Associate will conduct translational epilepsy research focused on the network mechanisms of ictogenesis in mesial temporal lobe epilepsy (MTLE). The researcher will develop and validate quantitative, event
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help reduce uncertainties in climate forecasts and better assess the effects of aerosols on atmospheric systems. The postdoctoral researcher's mission will be to develop and improve the WRF-Chem model
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, where different human actions can both increase or decrease flood risk. Current European projections of future flood risk under climate change do not consider these types of effects and other dynamic
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experimental enclosures with the ultimate aim of reconstructing the visual circumstances leading up to mate detection. The successful candidate will contribute to an Australian Research Council funded project
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: Molecular modelling and simulation experience during PhD Ability to present complex information effectively to a range of audiences Experience of manipulating and visualizing large datasets We value