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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our
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convective hazards. The model development will be aided by synthesizing observational data and high-resolution numerical simulations to gain new conceptual insights on cloud life cycles. Potential
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in engineering applications. This includes working with hybrid approaches that combine advanced damage models with machine learning-enhanced numerical simulations, and exploring how these approaches
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particular focus on transferability across heterogeneous energy systems and datasets. Validate and benchmark the developed models using building measurements, physics-based simulations and energy-system
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, acoustics, micro- and nanotechnology. We offer reservoir computing measurement setup, high frequency NEMS characterization platform, numerical simulators, and multiphysics environment. The recruited Postdoc
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, theoretical modelling and numerical simulations. The team focuses on model materials with controlled physical parameters, enabling quantitative comparisons between experiments, models and simulations, with
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is that our emotional and perceptual encounters with morally significant situations—moral experiences—are central to justified moral judgement, and can be harnessed in design. As the WP1 postdoc, you
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challenging, especially in dunes with complex topography. Your job In this 2-year postdoc position, you will use numerical modelling and machine learning techniques to increase the accuracy of coastal dune
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Postdoc in Developmental Psychology Faculty: Faculty of Social and Behavioural Sciences Department: Psychology Hours per week: 28 to 40 Application deadline: 1 November 2026 Apply now This 2.5
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together