Are you curious about transitioning into a career in data science? Do you want to hear more about the data science field or learn how to acquire the skills needed to become a data scientist in industry? Then you should join the first Northwestern Data Science Career Evening Workshop, which will feature both data science training programs and industry representatives from a variety of sectors.
Date and Location:
Friday, April 7, 2017
4:30 - 8:00 PM
Wieboldt Hall, Room 540
Kellogg School of Management, Northwestern University
340 E Superior St, Chicago, IL 60611
Organized by the Northwestern University Postdoctoral Forum (NUPF) and the Chicago Graduate Student Association (CGSA). Supported by The Graduate School Professional Development Grant, the Northwestern Institute on Complex Systems, and IDEAS.
For more information and to register, please visit: data-science-career-evening.org
Northwestern University currently hosts a significant number of faculty engaged and interested in data science. Some are in the methods disciplines (computer science, applied math, statistics) and many more are in domain disciplines across many schools. Many of these researchers are unaware of one another and there have not been opportunities for developing intellectual exchanges and focused discussions on data science research projects. The research of faculty here at Northwestern has demonstrated that strong interdisciplinary collaborations lead to increased scientific productivity and impact. Northwestern’s Office of the Provost and Office of Research have made a financial commitment in order to promote the strengthening of interdisciplinary collaborations around data science with the goal of moving Northwestern forward in this area. Importantly, we are defining data science (and “big data”) not by the absolute size of the data, but by its increase relative to what has been typical in a discipline.
As a result of the University’s commitment, the Data Science Initiative has been granted funds to support faculty already involved or planning to get involved in Data Science. Funds have been allocated for the retaining and hiring of postdoctoral fellows and for the support of current graduate students. We will support on the order of 15-20 data science projects per year at the level of $10K-$50K in direct costs.
View the Funding Programs page for more information.
Science of Science Chicago is a monthly meeting place for Science of Science in the Chicago area spanning different universities and campuses.
These meetings at Northwestern's Medical Campus are for people who are interested in research on Science of Science in the Chicago area. We hope to create a shared regular meeting place for scientific exchange and discussion across different universities, and university campuses, and different methodological approaches, and scientific backgrounds.
Whether you do active research on Science of Science or are just interested in that area, please feel welcome. Science of Science is a young discipline whose perspectives may be sociological, economic, data-scientific, bibliometric, network-scientific, genomic, or historic.
Find out more information at: science-of-science-chicago.org
Northwestern News Special Feature, May 2016
A tidal wave of digital information has ushered in a new era of computing and analysis in the 21st century. Data science, or "big data," is affecting every aspect of Northwestern’s learning and research enterprises — among other things, leading to breakthroughs in precision medicine; contributing to a revolution in astronomy with profound insights about the universe; transforming the scope and depth of social science research with significant policy implications, and fueling research about consumer behavior that is affecting how companies do business.
Visit Northwestern News to read more.
Wherever you look, there is talk of the revolution being brought about by "Big Data." But is Big Data just a fad, as its critics contend, or is there something at its core that is here to stay with us?
Well before the term was coined, particle physicists were driven to Big Data challenges by the necessity of their large-scale detectors and produced datasets. Now however, we live in a world where not just the amount, but also the diversity and complexity of digital information continues to grow exponentially. Materials simulations and astronomy images are pushing the boundaries of exploration. Social networks enable the exchange of information between people; medical devices and e-commerce record the exchange of information between people and machines; GPS devices and bar code scanners allow the exchange of information between machines.Read More...