Located in North Carolina's third largest city, UNC Greensboro is among the most diverse, learner-centered public research universities in the state, with nearly 18,000 students in eight colleges and schools pursuing more than 150 areas of undergraduate and over 200 areas of graduate study. UNCG continues to be recognized nationally for academic excellence, access, and affordability. UNCG is ranked No. 1 most affordable institution in North Carolina for net cost by the N.Y. Times and No. 1 in North Carolina for social mobility by The Wall Street Journal - helping first-generation and lower-income students find paths to prosperity. Designated an Innovation and Economic Prosperity University by the Association of Public and Land-grant Universities, UNCG is a community-engaged research institution with a portfolio of more than $67M in research and creative activity. The University's 1,100 faculty and 1,700 staff help create an annual economic impact for the Piedmont Triad region in excess of $1B.

The Nanoscience Department at the University of North Carolina at Greensboro seeks to hire a tenure-track faculty member at the rank of Assistant or Associate Professor in Computational Nanoscience. The Department of Nanoscience is a dynamic and transdisciplinary department that is graduate-only and research-intensive. The Department of Nanoscience offers several graduate degree programs including a Ph.D. in Nanoscience with concentrations in Synthetic Biology and in Advanced Materials; a thesis-based MS; and a Professional MS in collaboration with the Bryan School of Business and Economics. The department is located within the Joint School of Nanoscience and Nanoengineering, an institution joined between the University of North Carolina at Greensboro and North Carolina A&T State University.

Applicants who work in the field of computational physics or computational materials science and can complement, collaborate, and grow current research efforts in the department to build a strong computational nanoscience research program are welcome to apply. Of particular interest are those whose research programs will focus on solid-state physics, quantum computing, condensed matter physics, and the development of computer-based mathematical models (machine learning) for understanding, analyzing, and predicting the behavior or properties of systems relevant to nanoscience and nanotechnology, and develop algorithms and simulation tools to advance the state of the art in multi-physics simulation for a large variety of physical processes in 2D and 3D, where problems are not well defined; however applicants with strong background in solid state physics and working in the field of computational nanoscience, broadly defined will be considered.