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 Virginia Tech Department of Mathematics anticipates a tenure-track opening in High Performance Computational Mathematics with a start date of August 10, 2018, at our Blacksburg, VA, campus. The successful candidate will have a strong background in computational mathematics and high performance computing. Possible specialties include, but are not limited to, mathematical aspects of numerical linear algebra, randomized numerical linear algebra, inverse problems, numerical PDE modeling, PDE solvers, uncertainty quantification, scientific computing, scalable data analytics, or large-scale topological data analysis. Application areas of interest include, but are not limited to, geophysics, physics, biology, or economics.
The successful applicant will have the opportunity to collaborate with faculty across the university on the Intelligent Infrastructure for Human-Centered Communities Destination Area ( http://provost.vt.edu/destination-areas.html ). Priority areas of interest for this initiative include modeling, simulation, analytics, and decision-support environments that leverage modern high performance computing and big data for quantitative understanding of large-scale systems.
Appointment as an Assistant Professor of Mathematics is anticipated, but exceptional senior candidates will be considered for positions of Associate Professor of Mathematics or Professor of Mathematics. Teaching and service duties will be split between the Mathematics Department and the Computational Modeling and Data Analytics ( CMDA ) program. The CMDA program is a collaborative effort involving faculty members from several departments, coordinated by the College of Science's Academy of Integrated Science ( https://www.ais.science.vt.edu/index.html ). The college's Academy of Integrated Science and the university's Destination Areas are manifestations of Virginia Tech's commitment to its land-grant mission of using leadership in teaching, research, and service to address society's pressing problems.
The person appointed will have the following responsibilities:
•the development and maintenance of a distinguished research program with the potential for interdisciplinary impact;
•the continuing development of her/his own scholarly activities, professional capabilities, and service to the profession;
•active and effective participation in undergraduate and graduate instruction and student advising;
•active and effective participation in department and university administrative governance; and
•adherence to the responsibilities of the faculty as described by the faculty handbook (http://www.provost.vt.edu).

Required Qualifications:
To receive consideration, applicants must have:
-a Ph.D. in mathematics or a related field at the time of appointment; and
-an active research program or, for new Ph.D.'s, strong promise for developing an active research program.

Preferred Qualifications:
It is desired that candidates have:
-a record of achievement, as might be demonstrated during a postdoctoral or previous faculty appointment or by experience in a government or industrial laboratory;
-a research program in computational mathematics in areas such as computational science, algorithms for parallel computing, numerical PDE modeling, PDE solvers, uncertainty quantification, numerical methods for large scale physical simulation, scalable data analytics, large-scale topological data analysis, numerical linear algebra methods for exascale computing, large-scale graph algorithms, random algorithms, inverse problems, or deep learning, all with particular preference given to emphasis on the role of high performance computing;
-vision, creativity, and leadership skills relevant to research and/or instruction;
-the ability and willingness to develop cross-disciplinary research collaborations in areas relevant to the Intelligent Infrastructure for Human-Centered Communities Destination Area;
-demonstrated effectiveness or interest and potential in undergraduate and graduate teaching;
-the ability and willingness to include state-of-the-art computational principles and practices in undergraduate and graduate instruction;
-a commitment to teach and advise a diverse student body; and
-experience with computational problem solving using massively parallel computers, particularly if that experience involves developing software for high performance computing.



To apply please click here!