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anticipation. Unlike static distributions, these models should represent the spatiotemporal transition functions of human states—predicting how a person will move or interact with objects(/persons) based
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for integrating and interpreting data generated within digitally enabled postharvest systems, including distributed and near-real-time data streams. Investigate the potential role of data-driven and artificial
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center fully integrated into the LIGO/Virgo distributed computing network. IFAE is in a privileged position to analyze the LIGO/Virgo/KAGRA data and, in collaboration with IFAE’s teams in CTA/MAGIC and
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experience with DFT codes will be very highly valued. • Knowledge of chemical reactions and how to model them through computer simulations is highly valued. • Knowledge of classical molecular dynamics