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Classification Title: Post Doctoral Associate Job Description: A Post-doctoral Associate in Social Network Analysis position is available for up to 2 years to work within the NSF supported project
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emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity
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networks, with a focus on carbon emissions reduction and network telemetry. You will contribute to the development of a framework that reduces the carbon emissions of networks through the use of carbon-aware
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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crystalline resins for use in two-photon polymerization. New forms of imaging hardware will be utilized in collaboration with partners to provide greater understanding of the polymer network morphology and how
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understanding of the polymer network morphology and how it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid
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to develop applied research skills in machine learning, interact with an international network of collaborators, and gain post-doctoral research experience. The ideal candidate is self-motivated and can work
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on the networked interactions between stakeholders in regional innovation ecosystems and assessing effects of interventions in such networks. We are interested in understanding the role of stakeholders in the set-up
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including text mining, machine learning, network science, choice modelling, causal inference, and agent-based modelling with the aim of developing deeper, mechanism-based understandings of important social