24 communication-network-optimization Postdoctoral positions at Northeastern University
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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for the Modeling of Biological and Sociotechnical Systems (MOBS Lab) within the Network Science Institute at Northeastern University. MOBS Lab focuses on research projects aimed at developing innovative mathematical
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in the field of network science, with applications to nutrition, biological networks, network medicine, and the science of science. The position involves developing and applying computational
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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, the college collaborates across the university, the Northeastern network, and partners around the globe. The Writing Program at Northeastern University, housed in the College of Social Sciences and Humanities
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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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chloroplast protein-protein interactions network (Wang et al., Cell 2023; Wang et al., in preparation for submission). Qualifications: The ideal postdoc candidate must have a Ph.D. in plant science, molecular
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About the Opportunity The Communication for Health Equity Lab led by Professor Diane Francis is looking for a Postdoctoral Research Associate to help support the transdisciplinary research
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, data ethics, and statistical communication. We are also interested in investigating the rhetorical and communicative aspects of data communication. The candidate will lead projects around designing and
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, health economics, or a related field Strong communication and writing skills Experience in advanced epidemiologic and/or econometric methods to strengthen causal inference is strongly preferred The initial