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) Social Media Analysis (iii) Algorithmic Privacy, (iv) Analysis of Academic Collaborations, (v) Human-Bot interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD
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possible research topics include: (i) social media analysis, (ii) collaboration and teamwork, (iii) gender inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal
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interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD in one of the following: Data Science, Computer Science, Computational Social Science, Information
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inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science
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/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
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boundaries coevolve in multiplex communities; how attribute- and opinion-based cues shape insider/outsider categorization, intergroup relations, and social cohesion; and how to design interventions
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management Cognitive radio or adaptive communication systems, including dynamic spectrum access, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep
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on the physical layer design of wireless communication systems and explore enabling technologies for 6G and beyond wireless networks. Applicants must hold a PhD degree in electrical/electronics engineering
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, speech, images, and physiological signals. Preferred Experience: The lab highly values candidates with one or more of the following experiences: Human-Centered Applications: Familiarity applying ML in
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separation from frameworks. Excellent verbal and written communication skills, and excellent record of research accomplishments are preferred. Experience with modern sampling techniques such as metadynamics