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in postglacial RSL, and evaluate glacial isostatic adjustment (GIA) predictions against empirical data. The selected candidate will utilize the skills and expertise granted to them by their education
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projects to address the injury to marine mammal populations that occurred from the Deepwater Horizon oil spill. The incumbent will develop methods to use these data to estimate marine mammal occurrence
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. The position will involve working with large regional and global datasets, developing and applying quantitative models, evaluating environmental and productivity outcomes, and supporting the design and analysis
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: Molecular modelling and simulation experience during PhD Ability to present complex information effectively to a range of audiences Experience of manipulating and visualizing large datasets We value
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transformed into coordinated behavior and how sensory information contributes to the control and modification of movement. We combine experimental systems neuroscience with advanced behavioral analysis and
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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multilingual source material. You will have a strong understanding of deep learning and natural language processing, with practical experience of training, adapting and deploying large language models. You will
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extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
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with large regional and global datasets, developing and applying quantitative models, evaluating environmental and productivity outcomes, and supporting the design and analysis of case studies
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investigating large-scale circulation of the North Atlantic Ocean. The successful candidate will contribute to scientific research at the intersection of the RAPID-MOCHA and OSNAP observational arrays — two