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Interdisciplinary Training in Complex Networks and Systems
Understanding complex networked systems is key to solving some of the most vexing problems confronting humankind, from discovering how dynamic brain connections give rise to thoughts and behaviors, to detecting and preventing the spread of misinformation or unhealthy behaviors across a population. Graduate training, however, typically occurs in one of two dimensions: experimental and observational methods in a specific area such as biology and sociology, or in general methodologies such as machine learning and data science.
With more and more students seeking to gain sufficient expertise in mathematical and computational methods on top of domain-specific laboratory and social analysis methodologies, a greater demand for more efficient interdisciplinary training is emerging. The Indiana University National Science Foundation Research Traineeship (NRT) addresses this growing need with an integrated dual PhD program that trains students to be “bidisciplinary” in Complex Networks and Systems (CNS) and another discipline of their choosing from the natural and social sciences. It will seamlessly integrate traditional education with interdisciplinary hands-on research in a culture of academic and human diversity.
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The training program capitalizes on the new Indiana University Network Science Institute (IUNI). The Institute's 165+ faculty members will serve in interdisciplinary PhD program committees to be co-chaired by research mentors from both CNS and the target empirical domain. Project-driven, team-based research at IUNI will seamlessly integrate academic education with interdisciplinary hands-on scientific and industrial research. Trainees will learn to connect the general-purpose, computational expertise of CNS to the deep, domain-specific research methodologies of the natural, behavioral, and social sciences thus bridging the gap between distinct training cultures. They will be a new breed of STEM scientists that escapes the silos of disciplinary training to address the complex problems of the 21st century.
Applications Due December 1
For more information on how to apply please contact: [log in to unmask]. For information about research and academic components, please see our website https://cns-nrt.indiana.edu, contact the program director Prof. Luis M Rocha, or other members of the executive committee:
[log in to unmask]" alt="CNS-NRT Animated Logo" v:shapes="Picture_x0020_3">Executive Committee
· Luis M. Rocha, Director
· Katy Börner, Evaluation Committee Chair
· Bernice Pescosolido, Colloquia and Outreach Committee Chair
· Armando Razo, Education and Training Committee Chair
· Olaf Sporns, Recruiting and Admissions Committee Chair
· Tara Holbrook, Project Coordinator
Complex networks and systems
Social network science
Health & health care
Science of science
Finance and economy networks
Biological and chemical networks
$34,000 stipend on prestigious NSF Fellowship
Tuition and health insurance
Develop dual proficiency
Early integration in research via Indiana University Network Science Institute (IUNI)
National and international internships
Academic and industrial professional development including travel support
Diverse, collaborative cohorts
Interaction with world-renowned external board members and speakers
NSF fellow must be US citizens residents. IU fellowships and NRT affiliates available for international students.
Dual PhD program in CNS and another domain such as Biology, Chemistry, Cognitive Science, Economics, Psychological and Brain Sciences, Sociology, Political Science, Physics, etc. Hands-on training in general-purpose methodologies of CNS, computational and data science, as well domain-specific methodologies of a chosen natural, behavioral, or social science.
Luis Mateus Rocha, Professor of Informatics and Cognitive Science
Director, NSF-NRT Interdisciplinary Training in Complex Networks and Systems
Center for Complex Networks and Systems Research
School of Informatics, Computing, and Engineering
Indiana University, 919 E. 10th St
Bloomington IN, 47408, USA
Instituto Gulbenkian de Ciência, Oeiras, Portugal
Any analytical approach to understanding simplicity always turns out to be very complex. (Howard Pattee)