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appropriate field. You will work on the project “Data-Driven Micromagnetic Modelling”. Your job This study contributes to SPARK, an ERC Consolidator project that aims to unlock magnetic information stored in
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stakeholders. Your profile: PhD degree in materials science/engineering or related disciplines. Experience as experimental materials researcher in combination with modelling or data-driven methods is ideal
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simulations and data-driven models for optimizing electrolyte formulation. The project involves close interaction with experimental partners in the AFLOW consortium and includes a planned research stay at
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is passionate about shaping the future workforce in advanced and technology-driven construction sectors We are particularly interested in candidates with experience or research interests in areas
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traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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Ecole des Mines de Saint-Étienne | Gardanne, Provence Alpes Cote d Azur | France | about 13 hours ago
new therapeutic avenues for tissue engineering, regenerative medicine and inflammation disorders. This inflammation on a chip device is expected to become an essential model for studying immune cells in
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The University of Virginia Department of Mechanical and Aerospace Engineering invites applications for a Postdoctoral Research Associate focused on structure design to address critical healthcare
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient
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shaping the future workforce in advanced and technology-driven construction sectors We are particularly interested in candidates with experience or research interests in areas such as: Civil Engineering
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. This project will involve formalising and integrating the contributions of : (i) model-based and data-driven systems engineering (MBSE), (ii) embedded frugal (explainable and robust) AI, and finally (iii