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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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About the Opportunity SUMMARY The Network Science Institute (NetSI) is hiring one Postdoctoral Research Associate to join the newly formed Complexity & Society Lab (the “&-Lab”). The &-Lab is an
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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develop transformative therapies for glioblastoma (GBM) by understanding the disease on its own biological terms, within the complex context of the human central nervous system. We are entering an exciting
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
inequities, and other complex social problems. His research focuses on youth experiencing homelessness, where he has transformed the field's understanding of how social networks shape health and well-being
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Networks. Preferred Qualifications: ● Experience in quantum network experiments/devices. ● Experience in writing research proposals. ● Experience in supervising/guiding PhD and/or MS students
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vivo two-photon imaging of neural activity dynamics, imaging of neuromodulator releases, optogenetics, computational modeling of complex animal behaviors and neural dynamics, and network simulations
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on human trafficking, including supply chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data
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in network science. NetSI faculty and researchers are working to advance the understanding of complex systems through the lens of networks, and to apply this knowledge to solve real-world problems in a