In the Department of Mathematics at NC State University, a long tradition of excellent teaching and a supportive environment for students is coupled with cutting-edge research across a wide range of mathematics and its applications. Many members of the department are involved in interdisciplinary programs and research groups on campus and in the broader Research Triangle community.

The department’s research strengths include fundamental mathematical areas such as algebra, topology, and geometry, especially their connections to combinatorics, symbolic arithmetic, and mathematical physics; Fundamental areas of applied mathematics, including matrix factorization, numerical analysis, scientific arithmetic, probability, optimal control, ordinary, partial, and stochastic differential equations, and dynamical systems; and applications of mathematics to biology, finance, and industrial problems. Annual research funding exceeds $3 million, and supports numerous research grants for undergraduate and graduate students. More information about the department can be found at http:\\www.math.sciences.ncsu.edu. While working in this department, you will be expected to foster a supportive and welcoming environment.

NC State promotes an integrated approach to problem solving that changes lives and provides leadership for social, economic, and technological development across North Carolina and around the world. NC State’s land-grant mission of teaching, research, and service is dedicated to serving North Carolina and its people. Applicants are encouraged to review the institution’s mission, vision, and strategic plan, and to consider how their background, interests, and experiences will enable them to support the university.

The co-investigator will contribute to ongoing projects on BK virus. BK virus is a common infection in immune-compromised kidney transplant patients, in some cases leading to the loss of the transplanted kidney. There is no antiviral effective against BK virus, and standard practice is to reduce immunosuppression, which can itself lead to renal rejection; Hence, managing immunosuppression in these patients is a major challenge. In this project, we use existing datasets from collaborators at Duke University to develop mathematical models and optimal control algorithms for the dynamic interactions between the virus, the immune system, and the transplanted kidney.