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of bird genomes, working on some of the best-studied avian models (Mauritius parakeet, ringneck parakeet, red-crowned parakeet, and orange-bellied parrot). The PhD candidate will study data from
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Data-driven predictions of dynamical systems are used in many applications, ranging from the design of products and materials to weather and climate predictions. Mathematical concepts from geometry
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transmitted migration and a flexible diet, which facilitate rapid adaptation to changing conditions. Over the last decades, this species has been undergoing dramatic change, notably with important re-routing
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Technologies - Help Shape the Future of Clean Energy Storage! Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean
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, are crucial for modelling volcanic processes and are vital for understanding the transitions. Geophysical monitoring provides essential information to constrain these parameters and inform decision
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models. The project’s key objectives are to: 1) Identify critical indicators relating to ecosystem health and resilience; 2) Incorporate indicators into DBN models to simulate how ecosystems respond
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conditions, peloton strength, team strategy interactions, rider skills, and physiological capabilities during critical race moments. These elements are highly dynamic and interact to shape racing tactics and
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natural conditions in the laboratory. Marine phytoplankton, which act as the base of the marine food web and contribute to major global biogeochemical cycles, will be used as a model to understand
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applications. Understanding durability requires research into the effects of both manufacturing methods and environmental storage conditions on the material properties and performance over time. The aim
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loading conditions. By generating datasets from finite element simulations, ML models can learn the mapping between unit cell design parameters and homogenised properties. State-of-the-art approaches