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Field
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imaging datasets and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image
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modelling, enhanced sampling techniques, and multiscale approaches, alongside contributing to the development and improvement of robust scientific software. You will analyse data, refine hypotheses, publish
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success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential
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, or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when
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collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and
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force fields (MLFFs) that combine state-of-the-art equivariant neural network architectures with robust, well-calibrated uncertainty estimates. These models will enable fully automated active learning in
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strategies influence gut health, metabolism, the microbiome and resistome in pigs, aiming to improve robustness and disease resistance. The research methodology is mainly based on different molecular biology
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alignment, safety, and reliability frameworks to ensure LLM outputs are accurate, trustworthy, and robust in scientific contexts. Evaluate and benchmark LLM reasoning, cognitive capabilities, and
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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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transformer architectures for multimodal fusion (RGB + thermal, intraoperative video, OR signals, EHR, surveys); develop temporal and cross-attention components for longitudinal risk trajectories. Build robust