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, or similar, and a degree in Environmental Engineering, Environmental Science, or a related quantitative field. Position 2 will focus on large-scale data analytics and machine learning. Applicants should have
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of machine learning researchers, engineers, and domain scientists. This collaborative environment offers a unique opportunity to work on cutting edge AI models, with a focus on generalization and
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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developing cutting edge analytic tools for studying the genome transformation and genomic activities. 70% - The candidate will be mainly focusing on developing machine learning methods and/or AI algorithms
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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functions beyond protein production, with ongoing projects investigating the mechanisms of mRNA packaging and organization and their connections to human diseases. More information is available at https
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 7 days ago
methodology, machine learning, and biomedical data science. Our research develops rigorous and interpretable methods for high-dimensional biomedical data, with applications spanning cancer genomics
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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-physical systems security, protection of critical infrastructure, and adversarial machine learning. The position will involve collaborating with faculty and graduate students on interdisciplinary research
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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Appointing a postdoctoral scholar with expertise in causal inference, machine learning, and