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Tenure-Track Position in Machine Learning / AI

Position Type: 
Tenure-Track Faculty
Job Description: 

The Computer Science Department at Rutgers University invites applications for a Tenure-Track position in Machine Learning and/or AI. We are especially interested in an Assistant Professor but will also consider exceptional candidates at higher ranks.

The appointment will start September 1, 2019.

Rutgers University offers an exciting and multidisciplinary research environment and encourages collaborations between Computer Science and other disciplines.  Rutgers is located in the middle of the greatest concentration of industrial and government research laboratories in the US.  The surrounding major metropolitan areas also provide many cultural and social opportunities. Rutgers subscribes to the value of academic diversity and encourages applications from individuals with varied experiences, perspectives, and backgrounds.  Women, persons from underrepresented minorities, dual-career couples, and persons with disabilities are encouraged to apply. Rutgers is an affirmative action/equal opportunity employer.

Responsibilities will include: 

Responsibilities include research, teaching undergraduate and graduate level courses in different areas of Computer Science and supervision of PhD students based on funded projects.

Requirements: 

Applicants should show evidence of exceptional research promise with potential for external funding, and commitment to quality advising and teaching.  Hired candidates must complete their Ph.D. in Computer Science or a closely related field by August 31, 2019.

Contact Info: 

Questions should be directed to Komal Agarwal at kagarwal@cs.rutgers.edu.

Timelines: 

Applications received by January 14, 2019 will be given priority.

Rutgers: 
Rutgers, the State University of New Jersey, is an Equal Opportunity / Affirmative Action Employer. Qualified applicants will be considered for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, genetic information, protected veteran status, military service or any other category protected by law. As an institution, we value diversity of background and opinion, and prohibit discrimination or harassment on the basis of any legally protected class in the areas of hiring, recruitment, promotion, transfer, demotion, training, compensation, pay, fringe benefits, layoff, termination or any other terms and conditions of employment.