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advance the fundamental science of artificial intelligence and address some of the field's most important challenges. You will be responsible for researching and developing novel algorithms and techniques
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acoustic propagation that are applicable to a wide range of ocean environments. (40%) Lead efforts to translate propagation and uncertainty models into computationally efficient algorithms that can be
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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. Develop algorithms to identify specific seabed characteristics. Conduct independent research related to underwater active acoustics and seabed sensing. Collaborate with researchers from academia, industry
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study at the forefront of chronic pain epidemiology, helping to validate an algorithm for identifying neuropathic pain using linked healthcare data. Your work will generate evidence on prescribing
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, including prediabetes, type 1 and 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). Their research informs artificial pancreas algorithms and contributes to drug development targeting hepatic
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning