Connectionists: Job opening: TT Assistant Professor in AI/ML at Virginia Tech

[Bert Huang]

Folks,

Virginia Tech’s Department of Computer Science is looking for faculty in AI and ML. See the ad pasted below. Feel free to reach out to me with questions, as I’m on the search committee. I’ll also be at NIPS, if you want to discuss there.

Bert

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ASSISTANT PROFESSOR IN AI/ML

The Department of Computer Science at Virginia Tech (cs.vt.edu) seeks applicants for a tenure-track assistant professor position in artificial intelligence and/or machine learning.  Exceptional candidates at higher ranks may also be considered.

Candidates with core research interests in AI/ML are especially encouraged to apply. Some example areas include deep learning, reinforcement learning, natural language processing, probabilistic models, optimization, and learning theory, computing, and intelligent systems.



CANDIDATES
The successful candidate will join an active group of CS faculty in the AI/ML area, many of whom are members of the Discovery Analytics Center (dac.cs.vt.edu), which leads data science research on campus. CS faculty also collaborate in other interdisciplinary research groups, including the Center for Human Computer Interaction (hci.vt.edu) and the Center for Business Intelligence and Analytics (cbia.pamplin.vt.edu). Faculty participate in data analytics education initiatives (analytics.cs.vt.edu), including the Computational Modeling and Data Analytics (ais.science.vt.edu/programs/cmda.html) undergraduate program.

Computer Science also collaborates closely with many departments, including Electrical and Computer Engineering (ece.vt.edu) and Statistics (stat.vt.edu), and more broadly across the university, including with the Hume Center for National Security and Technology (hume.vt.edu) and the Biocomplexity Institute (bi.vt.edu). Successful candidates will have the opportunity to engage in transdisciplinary research, curriculum, and outreach initiatives with other university faculty working in the Data & Decisions Destination Area, one of several university-wide initiatives (provost.vt.edu/destination-areas).

Candidates must have a Ph.D. in computer science or related field at the time of appointment, and a rank-appropriate record of scholarship and collaboration in computing research.  They are expected to develop a nationally recognized research group. The successful candidate will be expected to teach graduate and undergraduate courses, mentor graduate students, and should support diversity in the campus community. Virginia Tech is committed to building a culturally diverse faculty and strongly encourages applications from traditionally underrepresented communities. 

The position requires occasional travel to professional meetings. The selected candidate must pass a criminal background check prior to employment.

COMPUTER SCIENCE AT VIRGINIA TECH
The department has 53 teaching faculty, including 47 tenured or tenure-track faculty, over 950 undergraduate majors, and over 250 graduate students. Departmental annual research expenditures over the last four years average $12 million. The department is in the College of Engineering (eng.vt.edu), whose undergraduate program ranks 13th and graduate program ranks 30th among all U.S. engineering schools (USN&WR).  This position is located at the main campus in Blacksburg, VA (blacksburg.gov), in a region that is consistently ranked among the country's best places to live.

HOW TO APPLY
Applications must be submitted online to jobs.vt.edu for posting #TR0180129. Applicant screening will begin on December 10, 2018 and continue until the position is filled. Inquiries should be directed to Dr. Edward Fox, Search Committee Chair, fox at vt.edu.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, gender, gender identity, gender expression, national origin, political affiliation, race, religion, sexual orientation, genetic information, or veteran status; or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees, or applicants; or any other basis protected by law.