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Tenure Track Positions
The Machine Learning Department of the School of Computer Science at Carnegie Mellon University invites applications for tenuretrack positions at the rank of Assistant Professor as well as positions at the level of Associate and Full Professor. All areas of machine learning and artificial intelligence will be considered. Applicants are expected to have an active research program and a commitment to teaching excellence.
The Department occupies a privileged position in the world of machine learning in part as the worlds first and possibly only academic Machine Learning Department. The Department has close relationships through shared faculty and active collaboration across the university especially with the Statistics Department the School of Public Policy and other academic units in the School of Computer Science including the Computer Science Department Language Technologies Institute Computational Biology Department Robotics Institute HumanComputer Interaction Institute and Software Engineering and Societal Computing. We seek applicants who will thrive in this interdisciplinary setting.
Carnegie Mellon is highly supportive of dual career candidates and strongly encourage them to apply.
We also particularly encourage applications from candidates who have a demonstrated track record in mentoring and nurturing female and underrepresented minority students.
Candidates with a commitment toward building an equitable and diverse scholarly community are particularly encouraged to apply. We continuouslyseek to improve the diversity of our studentstaff and faculty populations including and especially through annual faculty hiring processes. Our hiring committeethoroughly review the qualifications of every applicant and are particularly enthusiastic about applicants whose background and experiences would make them unique among our from candidates who have a demonstrated track record in mentoring and nurturing women and students from groups traditionally underrepresented in computer science are strongly encouraged.
Full Time