Based on the foundation of the Ted and Karyn Hume Center for National Security and Technology, Virginia Tech launched the Virginia Tech National Security Institute (VT NSI) in September 2021. With a presence in Blacksburg and the Washington, D.C., metro area, the institute aspires to be the nation's preeminent academic organization at the nexus of interdisciplinary research, technology, policy, and talent development, the national security institute will advance national security in pursuit of a secure America.
Motivated applicants are sought to join VT NSI as Research Assistant Professor, Research Associate Professor, or Research Professor in Artificial Intelligence and Machine Learning to support rapid growth in our body of programs in data strategies, test and evaluation, artificial intelligence assurance, digital engineering, and cyber analytics and operations. Rank will be determined based upon experience and credentials. The winning candidates can expect highly competitive salary and benefits in a university setting. This position serves as a research staff member of the Hume Center and in the Intelligent Systems Division (ISD). ISD hosts a range of dynamic research projects and the successful applicant will have the ability to contribute to these programs, lead the development of new programs, and mentor students engaged in these programs.

Specific responsibilities include the following: (1) support the execution of university sponsored programs by conducting research and development; (2) author technical documents and publish peer-reviewed academic papers; (3) support the development of new funded research programs by participating on proposal teams and supporting the business development activities of VT NSI; (4) support the development and growth of the future AI workforce through student mentoring and advisement, and workforce training and education.

We are seeking individuals with expertise in artificial intelligence and machine learning to include at a minimum some of the following: supervised learning, unsupervised learning, deep learning, reinforcement learning, and generative AI. Successful applicants will have experience applying these machine learning methods to complex organization and/or system technologies.