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The Yale Institute for Network Science (YINS), the Yale Center for Research
Computing (YCRC), and the Department of Statistics and Data Science at Yale
(DS^2) will be hosting a network science-focused datahack at Yale
University on February 18-19, 2017. *Graduate, doctoral and postdoctoral
students in the fields of network science, data science, statistics, data
visualization, and related disciplines are invited to* *apply to compete at
Datahack@Yale 2017*. Student and postdoc network science pros will compete
to solve the challenge of their choice devised by Yale faculty and
corporate sponsors. Applicants from other academic institutions are welcome.

Working with network data is uniquely challenging, as it requires network
scientists to incorporate disparate methods from across disciplines
to answer questions about the interconnected world. The primary function of
this event is to bring together junior scholars from all levels
(undergraduate, graduate, doctoral and postdoctoral) who are interested in
network science, know the tools and methods, and want to solve problems and
produce useful insights in a highly collaborative and dynamic environment. *Day
one of the event (February 18) will be focused on exploring the data, and
attempting to answer the challenges posed by Yale faculty and corporate
sponsors. Day two of the event (February 19) will be devoted to data
visualization, as teams, *with the help of design mentors, *discover how to
best convey their challenge solutions. * Following the visualization
component, our panel of judges from academic and corporate life will award
prizes for the best project solutions.

Sponsors are interested in recruiting and are offering sponsored prizes.
Teams are comprised of no more than four individuals. All registered
attendees of Datahack@Yale 2017 will be granted access to Yale’s High
Performance Computing (HPC) cyberinfrastructure.

*You are invited to apply online at

Not a student but interested in being involved? Drop us a line and tell us
your vision [log in to unmask]

Warm regards,

Emily Hau and the Datahack@Yale Team

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