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Position Summary:
The Bradley Department of Electrical and Computer Engineering at Virginia Tech seeks applications for a tenured/tenure-track position in Computer Engineering, at the rank of Assistant or Associate Professor, specifically in the area of perception for autonomous systems, including (but not limited to) deep learning, knowledge representation & reasoning, reinforcement learning, reasoning under uncertainty, and their applications to perception in robotics and autonomy. This position is based in Blacksburg, Virginia.
The successful candidate will be expected to develop and maintain a vigorous, nationally recognized, funded research program. There are rich opportunities for collaboration with existing strengths across the University. The successful candidate will also be expected to teach undergraduate and graduate courses, and participate in service and outreach activities for the Department, College, and/or University. More broadly, the successful candidate should contribute to Virginia Tech's growing strength and leadership in Machine Learning research, education, and outreach.

Required Qualifications:
- An earned Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field, completed prior to employment
- Effective communication skills
- Demonstrated excellence in research, scholarship, and teaching, or evidence of high potential for such excellence
- Ability to articulate a coherent agenda of research and scholarship, and to identify potential funding sources to support such research
- Willingness and ability to work in a technology-based research and education environment, such as is characterized by use of learning technologies, distance learning, online courses, video-conferencing, and network and grid-based collaborative research

Preferred Qualifications:
- Prior experience in the role of PI or Co-PI on funded research projects
- Ability and willingness to work collaboratively with faculty from a variety of disciplines
- Interest or experience in mentoring students, both undergraduate or graduate, in research
- Interest or experience in working effectively with a diverse student population



To apply please click here!