Applications are invited for a Research Assistant Professor position with the Sanghani Center for AI and Analytics at Virginia Tech, Blacksburg, VA.
Type: Full-Time
Posted: 02/13/2024
Category: Computer Science
Job Description
Applications are invited for a Research Assistant Professor position with the Sanghani Center for AI and Analytics at Virginia Tech. The center works on machine learning and knowledge discovery with applications to important areas of national interest. Currently, active projects at the Sanghani Center are sponsored by NSF, DARPA, the DoD, and various industry partners.
This position especially seeks a candidate conducting research at the intersection of software engineering (including testing, reliability, and verification/validation) and machine learning/artificial intelligence. In particular, the candidate will help develop systems and conduct research in automated T&E (test and evaluation) of machine learning algorithms as they are deployed in practice in production contexts.
First, the candidate will interface with the Sanghani Center’s faculty and students, as well as our collaborators/sponsors, to study, research, and lead implementations of machine learning algorithms, ensuring continual and error-free deployment and assessment on an ongoing basis. Second, the candidate will stay abreast of current literature and develop assessments of machine learning algorithms going beyond performance/accuracy, including other facets of risk such as stability, drift, fairness, and adversarial robustness.
Work led or done by the candidate is expected to be published in machine learning venues (such as NeurIPS, ICLR, and KDD) as well as software engineering venues. To this end, the candidate is expected to supervise software engineers, PhD students, and undergraduate students toward research objectives.
Finally, the candidate will contribute to the communications and outreach mission of the Sanghani Center by documenting a framework for T&E that can be utilized by all Sanghani Center members and collaborators. This facet will also involve presentations and communications with our sponsors. While the candidate will be based in the National Capital Region (NCR) in Arlington, Virginia, and working in a hybrid mode, he/she is expected to engage in collaborative research across the different campuses of VT (e.g., between Blacksburg and NCR campuses) and with the Sanghani Center’s partners inside Virginia Tech (e.g., the NSI) and outside Virginia Tech (from both academia and industry).
The Sanghani Center offers plenty of opportunities for research publication and career advancement. The successful candidate will have opportunities for joint co-authorship of key publications in data analytics, access to the rich portfolio of data holdings from the Sanghani Center’s projects, and the excitement of participating in cutting-edge data analytics research. In addition, the candidate will have access to the numerous graduate program offerings at Virginia Tech in this space, e.g., graduate courses and specializations offered by Sanghani Center faculty.
The candidate will report to the Center Director.
Required Qualifications
- PhD in Computer Sciences/Computer Engineering with emphasis on research at the intersection of software engineering and machine learning.
- Post-doctoral experience conducting test and evaluation (T&E) of data analytics pipelines and/or machine learning systems in production environments.
- Publications in leading software engineering (e.g., ICSE) and machine learning (e.g., NeurIPS, ICLR, KDD) venues.
- Credentials aligned to the rank of a research assistant professor.
Preferred Qualifications
- Interest and/or experience in working effectively with a diverse faculty, staff, and student population.
- Experience conducting research programs supporting defense and intelligence sponsors.
- Experience mentoring graduate students.
Appointment Type
Restricted
Salary Information
$100,000-$105,000 annually
Review Date
02/29/2024
Additional Information
The successful candidate will be required to have a criminal conviction check.
Apply on the Institution’s Website.
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