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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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the computational science community. We empower researchers to tackle some of the most complex global challenges through our unique blend of supercomputing resources and computational science expertise. The ALCF is
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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transportation networks. In particular, the successful candidate will conduct cutting-edge research in: Adaptive incentive mechanism design for complex sociotechnical systems Strategic learning and equilibrium
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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 wide range of fields, including urban science, public
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optogenetic investigations of cognition-related hippocampal formation and related brain networks. ? Analysis of electrophysiologically-evoked responses to assess synaptic population changes
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University of North Carolina at Greensboro | Greensboro, Indiana | United States | about 5 hours ago
institution in North Carolina for net cost by the N.Y. Times and No. 1 in North Carolina for social mobility by The Wall Street Journal — helping first-generation and lower-income students find paths
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) experience with neural network training and language model fine-tuning; (2) background in natural language processing, linguistics, and/or human reasoning; (3) strong coding skills; and (4) strong
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of brain network representations, with a specific focus on the development and emergence of psychopathology. The successful candidate will contribute to the development and application of computational
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medicine through our discoveries of today. At locations in Berlin-Buch, Berlin-Mitte, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease