SIAM's Newest Journal - Mathematics of Data Science
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Data Science

This research area covers mathematics and computational methods in data science that includes machine learning and data mining, intertwined with other key areas such as statistics, computer science, network science, and signal processing - all within the context of data science as well as applications of mathematical methods in data/information processing to science and engineering problems.

Upcoming Conferences

Analytic Algorithmics and Combinatorics (ANALCO19)

January 6 - 7, 2019
San Diego, California, USA
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SIAM International Conference on Data Mining (SDM19)

May 2 - 4, 2019
Calgary, Alberta, Canada
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What's New

What's New


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Opportunities

We know it can be overwhelming to keep track of career opportunities that may be relevant to you as a member of the SIAM community. So, we’ve compiled lists of some of our favorite fellowship, internship, and research opportunities. Check ‘em out!

Fellowships

Looking for financial support to further your research? Fellowships often provide funding plus experiential learning opportunities to young researchers. Learn more about fellowship opportunities.

 

Internships

Internships allow you to network and forge connections for future job possibilities, while also exploring possible areas of interest. Look at this list of companies who offer valuable opportunities.        

 

Research Opportunities

Our community is founded on igniting groundbreaking developments in applied math and computational science. Take a deeper dive into your area of study with one of these opportunities.

 

Activity Groups and Journals

Related Activity Group

  • Data Mining and Analytics
The purpose of this activity group is to advance the mathematics of data mining, to highlight the importance and benefits of the application of data mining, and to identify and explore the connections between data mining and other applied sciences.

Related Journal

  • Mathematics of Data Science

SIAM Journal on Mathematics of Data Science (SIMODS) publishes work that advances mathematical, statistical, and computational methods in the context of data and information sciences. We invite papers that present significant advances in this context, including applications to science, engineering, business, and medicine.

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