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Description The Center for Interacting Urban Networks, New York University Abu Dhabi, seeks to recruit a Postdoctoral Researcher to support a project studying the Center’s research theme
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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focused on understanding and countering harmful narratives and, mis/disinformation, and applying social network analysis. To be successful you will need: PhD in a relevant discipline such as computer
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regressions, Bayesian analyses). You preferably have experience supervising and/or teaching students. You preferably have knowledge of swarm robotics and/or deep learning artificial neural networks (e.g. CNN
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
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fresh perspective on how specialized brain networks can identify and categorize causes of sensory inputs, integrate information with other networks, and adapt to new stimuli. It proposes that perception
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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statistical approaches. A fundamental understanding of Deep Neural Networks as applied to high-frequency time series datasets, including the ability to design and implement custom NN models in PyTorch, as