Virginia Tech is a public land-grant university, committed to teaching and learning, research, and outreach to the Commonwealth of Virginia, the nation, and the world. Building on its motto of Ut Prosim (that I may serve), Virginia Tech is dedicated to InclusiveVT-serving in the spirit of community, diversity, and excellence. We seek candidates who adopt and practice the Principles of Community, which are fundamental to our on-going efforts to increase access and inclusion, and to create a community that nurtures learning and growth for all of its members. Virginia Tech actively seeks a broad spectrum of candidates to join our community in preparing leaders for the world.

Position Summary:
The Department of Computer Science at Virginia Tech (www.cs.vt.edu) seeks applicants for two tenure-track assistant professor positions in data analytics. Exceptional candidates at higher ranks may also be considered.
Candidates with research depth and breadth in data analytics, data mining, machine learning, deep learning, artificial intelligence, text mining, natural language processing, information retrieval, interactive visual analytics, data visualization, high-performance analysis, social informatics, or data science are encouraged to apply. Candidates working at the intersection of data analytics and other computing or application domains-such as cyber-security, urban computing, health analytics, bioinformatics, and distributed and IoT systems-are also encouraged to apply. Successful candidates should be able to demonstrate an interest in initiating and sustaining collaborations within computing as well as with data domain scientists.
Successful candidates will have the opportunity to engage in transdisciplinary research, curriculum, and outreach initiatives with other university faculty working in the Data & Decisions destination area, one of several new university-wide initiatives at Virginia Tech (provost.vt.edu/destination-areas). Data & Decisions is focused on advancing the human condition and society with better decisions through data. Faculty collaborating in this area integrate data analytics and decision sciences across the transdisciplinary research and curriculum efforts at Virginia Tech. Candidates with demonstrated experience in interdisciplinary teaching or research that aligns with the Data and Decisions vision (provost.vt.edu/destination-areas/da-overview/da-data.html) are especially encouraged to apply.
The Department of Computer Science is home to the Discovery Analytics Center (dac.cs.vt.edu), which leads big-data analytics research on campus. Data analytics faculty collaborate in interdisciplinary research groups, including the Center for Human Computer Interaction, the Center for Business Intelligence and Analytics, the Social and Decision Analytics Laboratory, and the Network Dynamics and Simulation Science Laboratory. Faculty also participate in data analytics education initiatives (analytics.cs.vt.edu), including the Computational Modeling and Data Analytics undergraduate program.
Candidates must have a Ph.D. in computer science or related field at the time of appointment and a rank-appropriate record of scholarship and collaboration in computing research, broadly defined. Successful candidates should give evidence of sensitivity to issues of diversity in the campus community and will be expected to teach graduate and undergraduate courses, mentor graduate students, and develop a high quality research program. Virginia Tech is committed to building a culturally diverse faculty and strongly encourages applications from women and minorities. The positions require occasional travel to professional meetings. Selected candidates must pass a criminal background check prior to employment.
Applicant screening will begin on December 1, 2017 and continue until positions are filled. Inquiries should be directed to Dr. Chris North, Search Committee Chair, north@cs.vt.edu.

Required Qualifications:
• An earned Ph.D. in computer science or a closely related field.
• Record of significant research accomplishments, e.g., publications.
• Ability to contribute to the department's teaching mission.

Preferred Qualifications:
• Demonstrated interest in collaborative research with existing
departmental research strengths.
• Demonstrated ability and willingness to work collaboratively with
faculty from a variety of disciplines.
• Contributions to improving the diversity of the discipline, and experience in working effectively with a diverse student population.
• Recognition of research excellence, e.g., best paper or society awards.



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