Careers

Carnegie Mellon University's Language Technologies Institute (LTI) seeks applicants for the Teaching track starting in the Fall 2027 semester. Teaching-track applicants must have strong interests and accomplishments in teaching, with expertise in language technologies.

The LTI is dedicated to the study of human language and related information technologies, including NLP, speech, MT, computational linguistics, text mining, machine learning, multimodality, multilingual NLP, and multimedia.  The LTI has some 30 faculty, about 125 PhD/MS research students, and 357 professional MS students. It has six degree programs, ranging from undergraduate to PhD. It is one of seven departments within SCS, which has over 250 faculty with expertise spanning all areas of computer science. SCS is a highly collaborative and uniquely interdisciplinary environment that promotes innovation and entrepreneurship in both teaching and research.

Candidates with a commitment toward building a scholarly community are particularly encouraged to apply. Our hiring committees thoroughly review the qualifications of every applicant. Applicants must have outstanding academic credentials and have an earned Ph.D. in Computer Science or a closely-related field.

This position includes teaching lecture style courses, project courses, seminars, and on-line courses supported by learning management systems (LMS) such as Canvas and Piazza. Candidates with industrial experience in language technologies and experience managing and conducting applied research with current technologies are encouraged to apply.

The teaching track is a career-oriented, renewable appointment with an initial appointment of three years. Typically initial appointments are at the rank of Assistant Teaching Professor, with the possibility of promotion to the ranks of Associate Teaching Professor and Teaching Professor. Teaching track positions are not tenured. The position provides substantial opportunities for professional growth and long-term contributions to education at Carnegie Mellon University both in person and online.

The full application should include:

• A brief letter of application
• Detailed curriculum vitae
• Teaching statement that describes the candidate's interests in teaching Carnegie Mellon students

• Evidence of teaching quality, including teaching evaluations, video samples of teaching, curriculum portfolios, or other evidence of commitment to teaching effectiveness

• Please provide a brief statement highlighting your past experience with, or future plans for, having a broad impact on CMU. In this statement you might consider telling us about unique curriculum design or how you broaden the distribution of your research results. We are interested in learning anything you wish to share about you, or your work as a future member of our faculty that demonstrates the potential to broaden participation in computer science, or more generally benefit CMU.

• Names and email addresses of three to five individuals who have been asked to provide letters of reference

Please apply via the CMU School of Computer Science online application: 

https://apply.interfolio.com/189576

For More Information, Contact:

Eric Nyberg | en09@andrew.cmu.edu

The Language Technologies Institute (LTI) in the Kenneth C. Griffin School of Computer Science (SCS) at Carnegie Mellon University invites applications for multiple tenure track faculty positions, with multiple positions starting in the Fall 2027 semester. Tenure-track applicants must have strong interests and accomplishments in both research and teaching.

The LTI is dedicated to the study of human language and related information technologies, including NLP, speech, MT, computational linguistics, text mining, machine learning, and multimedia. The LTI has some 30 faculty, about 125 PhD/MS research students, and 357 professional MS students. It has six degree programs, ranging from undergraduate to PhD. It is one of seven departments within SCS, which has over 200 faculty with expertise spanning all areas of computer science. SCS is a highly collaborative and uniquely interdisciplinary environment that promotes innovation in both teaching and research.

We seek candidates internationally who have a demonstrated commitment to excellence, and who will contribute towards building an equitable, diverse, and collegial scholarly environment. Applicants must have outstanding academic credentials and have an earned Ph.D. in Computer Science or a closely related field.

Excellent candidates in all areas of natural language processing and related language technologies are encouraged to apply, including:

• Large language models (all aspects, including training, evaluation, systems)
• Interactive systems and conversational AI
• Multimodality
• Domain-specific applications (e.g. healthcare, education, legal, computational social science)
• Impacts of language technology on society (e.g. future of work, policy implications)

The full application should include:

• A letter indicating the research area
• Detailed curriculum vitae
• Research statement (including both current and future directions)
• Teaching statement
• Broader impact statement describing how your research and teaching has an impact on society, particularly for underrepresented groups (see full prompt)
• Copies of 3 representative papers
• Names and email addresses of three to five individuals who have been asked to provide letters of reference

Carnegie Mellon University shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability.

Please apply via the CMU School of Computer Science online application: 

https://apply.interfolio.com/189576

For More Information, Contact:

Eric Nyberg | en09@andrew.cmu.edu