The Network Science PhD program is a pioneering interdisciplinary program that provides the tools and concepts aimed at understanding the structure and dynamics of networks arising from the interplay of human behavior, socio-technical infrastructures, information diffusion and biological agents. Students will be able to work with some of the most prominent network scientists in the world and can participate in cutting edge research activities and work with unique large-scale network datasets. Students will interact and work with members of the network science community representing a wide range of fields, including computer science, information science, complexity, physics, sociology, communication, organizational behavior, political science, and epidemiology.
Working across traditional boundaries, researchers have begun to accelerate the integration of theoretical ideas and research technologies under the set of ideas and approaches that have recently been referred to as Network Science. Research on network connections among multiple types and levels of “actors” offers a potentially powerful mechanism to understand the workings of complex systems across broad areas of science. This perspective requires novel evaluations of, reconfigurations in, and innovations for standard methods of theorizing, data collection and analysis. In order to provide training for the next generation of network scientists that couples deep disciplinary knowledge with interdisciplinary Network Science, the PhD program is built on the following core principles:
• In-depth training in disciplines and programs essential to interdisciplinary research. Current concentrations are focused on the physical sciences (physics); social sciences (political science); health science (epidemiology); and computer and information sciences. Additional concentrations may be added in the future.
• Common, foundational training in all aspects of Network Science (e.g., approaches, languages, problems) beginning in the first year of graduate training to build an inherently interdisciplinary science and the next generation of researchers.
• Learning to combine theoretical/substantive questions with the appropriate tools and techniques for data collection and analyses. A key element will be combining ideas, techniques, and collaborations into the novel interdisciplinary approaches that are paramount to Network Science.