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Field
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skills and curiosity about complex systems. Position Overview You will design and implement new computational and statistical models to reverse-engineer causal networks from noisy, high-dimensional, multi
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medicine, complex disease mechanism, systems pharmacology, bioinformatics, and network science/statistical physics. This position at Northeastern University may include opportunities to collaborate with
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, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis
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management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we
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, and analysis by using concepts and methods from machine learning, including pattern recognition, graphs, and complex networks. ** Specific Research Areas: * Develop concepts and algorithms to analyze
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conditions and network types. Visualising complex neural data: You will create sophisticated visualisations of high-dimensional neural network data and perturbation responses, translating complex computational
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properties across different conditions and network types. 3. Visualising complex neural data: You will create sophisticated visualisations of high-dimensional neural network data and perturbation
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G
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, and social networks, cluster within families, and how they, in combination with molecular profiles, relate to the physical living environment, health outcomes, and lifespan. This knowledge will then be