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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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network attractors, funded by The Leverhulme Trust. This is a brain inspired project in the field of Neurodynamics. Networks of oscillators are ideal candidates for modelling patterns of functional
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identification of biological sounds using passive acoustic data. Passive acoustic monitoring will be conducted with species identification based on a neural network trained and tuned to the turbulent waters
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, you will leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modeling systems as graphs and encoding nonlinearities in these. As
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-ray Photon Correlation Spectroscopy (XPCS) and Dynamic Light Scattering (DLS) techniques to study the dynamics of proteins in solutions and of their crystallization in bulk and at interfaces. Neural
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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communications. Evaluation of model performance can be conducted based on the data collected through the water tank. We have the GPU machines ($14k) to develop deep neural networks for underwater communications
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, accurately and securely. Goal of this PhD project High-capacity neural models, such as transformers, have been pivotal for establishing general-purpose models for a wide variety of natural language tasks
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to work in. Research groups: Computational Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science
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interested in conducting mathematical research that combines its theoretical rigor and beauty with real-world applications, including climate and weather, the formation of opinions and neural networks