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. This project will use state-of-the-art live-cell super resolution microscopy and automated image analysis to both visualise the 3D architecture of keratin networks in epithelial monolayers. You will explore how
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analyse both existing panel data and newly collected survey data (e.g. with multilevel regression and longitudinal panel analysis). We will refine existing network measures to better capture inherited
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Systems (GIS) and large-scale spatial and environmental pattern analysis. They will also be responsible for participating in soil sampling teams and in the design of large-scale monitoring networks. With
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in electrophysiological methods. We collaborate with a network of local mental health centers for recruitment of patient populations. The fellow will be involved in all aspects of research including
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on the track of Cyber-Human Physical Systems seeks researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber
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Preference will be given to those with proven knowledge and experience in undertaking research related to social network analysis. For the project information and job inquiries, please contact the Principal
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, resilient networking and fault-tolerant systems (detection, isolation, recovery). Proficiency in Python for rapid prototyping, data analysis, and simulation (e.g., NetworkX, numerical optimization, agent
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, Air quality, PFAS, Particles, Non-target analysis, Data analysis. Location of the PhD project: UPVD (Université Perpignan Via Domitia), Perpignan, France: 1st year of the PhD INERIS, Verneuil-en-Halatte
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an interdisciplinary environment; Willingness to travel within Europe for network activities and secondments (including research stays at i3S, Portugal). Desirable Experience in glycan analysis or glycomics workflows
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interpretation of experimental data; Teamworking experience; Publication record commensurate with career stage. Demonstrate proficiency with data analysis tools (e.g., Python/Matlab/Origin). Have the ability