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. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This limits the ability to optimize energy storage use for critical
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the complexity further to effectively plan their movement and deployment. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
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processes that are examined in a number of different fields of research, namely first and second language acquisition and processing and language change. Currently, each field employs different models
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, is organised as a section at the Department of Geosciences. PHAB’s main goal is to develop predictive models to identify habitable planets around other stars. Within three different research themes: (1
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and magnetic data to map subsurface structures 3. Basin modelling, with knowledge of sedimentary processes and tectonic evolution The project would contribute to mapping the thickness of sedimentary
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
, computation, and experiments to model and manipulate the physical forces experienced by invading cancer cells. The overarching goal is to identify biomechanical “weak points” in cancer cell invasion and to
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
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exhibit hallmarks of active matter. This PhD project aims to develop theoretical and computational active-matter models of early mouse embryogenesis that couple collective cell mechanics with gene
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neutron scattering (SAXS/SANS) along with theoretical model analysis including the use of multi-scale and artificial intelligence models. The PD will work closely with both the PhD candidates and PIs within