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aspects of the project, including analyzing near-Sun observations of CMEs and shocks, running three-dimensional numerical simulations to model the Sun-to-planet evolution of CMEs and their sheath regions
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the development of a phase-field model to study the mechanisms of formation and growth of tetrataenite (Ni-Fe with the L1₀ ordered structure) during cooling. The objective is to incorporate the presence
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CNR - ISTP (Consiglio Nazionale delle Ricerche - Istituto per la Scienza e Tecnologia dei Plasmi) | Italy | 17 days ago
astrophysical plasmas; iv) Theoretical and numerical modeling of space and astrophysical plasmas; v) Analysis of experimental measurements obtained by in‐situ satellites in the heliosphere. Preference is given
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research focused on biomedical image computing. Our work involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim
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well as emerging materials. These experimental techniques will be complemented by advanced electromagnetic modelling. Responsibilities and qualifications The ideal candidate will possess demonstrated expertise in
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the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. - Publication of research results and presentation of results at scientific conferences
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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, physical modelling experiments, field investigations, and/or numerical modelling. The specific focus area for the research can utilize any of these tools, or their combinations, and will depend
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possess strong programming skills in Python and C++, with experience in PyTorch and pybind11 for developing and optimizing deep learning models. Familiarity with Sentinel-2 satellite imagery and experience
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microenvironment, and other biological processes. Conduct preclinical studies using in vivo disease models (cancer, inflammation, organ injury, etc.) and new alternative methodologies (advanced biological models