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models. We further propose to develop scalable structure learning methods for these new models, including latent variable identification, and to demonstrate their effectiveness on real data. For this, we
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models for intelligent environments. The primary area of research involves developing AI models that can learn to represent real-world phenomena based on various types of observations, including video
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tuition assistance and reimbursement Commuter benefits, discounts and campus perks Learn more about these and additional benefits on our Benefits & Wellbeing Page . EEO/Non-Discrimination Commitment
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models and observations yet still rely heavily on precomputed risk maps. Deep learning has improved flood mapping, but many models remain event-specific and transfer poorly between regions. Geospatial
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better world and solutions that can change everyday life. Department of Information Security and Communication Technology Research is vital to the security of our society. We teach and conduct research in
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to inform experimental design and site selection, a series of studies will focus on learning about how fish use saltmarshes and seagrass in South Wales. Research findings will extend our understanding beyond
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distribution, which lead to an extremal analogue of Gaussian structural causal models. We further propose to develop scalable structure learning methods for these new models, including latent variable
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to support your PhD trajectory. Your supervisors will be Dr Catrien Notermans, Dr Sonja Marzi, Dr Elke Linders. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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Willingness to combine wet-lab experimental work and computational analysis Basic knowledge of statistics and/or programming (R, Python, or similar) Strong motivation to learn new techniques across