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contribute to an interdisciplinary collaboration focused on building construction to improve affordability, productivity, energy efficiency, and resilience. The candidate will be part of the UT-Oak Ridge
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell
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rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very relevant. The steps in the development of surrogate models are building data-driven models from medical imaging
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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that can stand in for slow model simulations. These tools will be used to test how model parameters influence results and to make parameter estimation more efficient. The project will apply and evaluate
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to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly those described by which offer a promising architecture for modelling
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initiatives are methodologically robust, inclusive, and impactful. This expert-driven initiative builds on over 30 years of CTN’s experience in providing methodological and statistical support, now expanding to
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passion for teaching computers how to see, have done some previous research in this field (e.g., internships, research papers, etc.), and want to make an impact in a societally relevant application. In your
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., internships, research papers, etc.), and want to make an impact in a societally relevant application In your application, please include a statement of research interest, CV, copies of exams, degrees and grades
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Work Where You Learn: Build Experience, Grow Skills, and Contribute to Your University Community. This position is available only to enrolled American University students. Important guidance