Carnegie Mellon University: Post-Doctoral Associate (9684)

The incumbent will conduct research related to challenges arising from analyzing large-scale social networks. This will include optimizing existing and developing new centrality and grouping algorithms for big data. In the context of dynamic network data and streaming data, change detection algorithms will be developed. The incumbent will work in existing research projects with the Research faculty member supervisor in the above mentioned areas; the work will focus on doing research and writing papers on the results. We are looking for someone who can start on or around February 1, 2013.

Education: PhD in Computer Science, Statistics, Mathematics, or with a strong emphasis on Social Network Analysis. Experience: Experience in handling large data sets and in writing scientific articles. Strong background in Network Analysis and its methods and algorithms.

Skills: Excellent verbal communication and good written skills. Physical Mobility: normal sedentary, but travel across campus, across town, and out of town may be required.

Mental: excellent analytical problem solving and organizational skills;
ability to comprehend system and application related materials; able to understand and follow directions; ability to work under pressure; pay attention to detail; meet flexible deadlines.

Minimum Education Level: Doctorate or equivalent

Advisor: Assistant Research Professor Dr. Jürgen Pfeffer

Organization: Institute for Software Research, School of Computer Science, Carnegie Mellon University

Primary Location: United States-Pennsylvania-Pittsburgh

FT/PT Status: Regular Full Time, Special Faculty

Salary: 50000-55000 US Dollars Annually

Fringe Benefits:


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Job Position 9684