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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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interaction networks that contribute to the pathogenesis of these diseases. This is a full-time, non-tenure-track position working in the Laboratory of Molecular Therapeutics. The appointment is annually
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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key regulators of inflammation and tissue remodeling in gut and skin diseases. • Apply and refine AI/ML methods, including deep learning, neural networks, and interpretable models (e.g., SHAP, BioMapAI
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convolutional/neural networks Experience with explainable and interpretable AI (XAI) Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University’s rules
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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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, 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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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