Assistant/Associate Professor of Linguistics (University of Texas Austin)

Department of Linguistics – The University of Texas at Austin Start date: Fall 2026–27 Rank: Tenure-track Assistant Professor or Associate Professor with tenure Description The Department of Linguistics at The University of Texas at Austin invites applications for a position in computational linguistics to begin Fall of academic year 2026–27, at either the rank of tenure-track Assistant Professor or Associate Professor with tenure. We seek candidates whose work develops computational methods in any area of linguistics and specifically connects linguistics to artificial intelligence, with particular interest in candidates who can interface with any of our current major areas of research in syntax, semantics, pragmatics, sounds, psycholinguistics, cognitive science, language documentation, historical linguistics, sign language linguistics, or sociolinguistics. Duties will include research, service, and teaching linguistics courses at all levels (lower- and upper-division undergraduate, and graduate), and training the next generation of researchers working in AI, natural language processing and machine learning, and computational methods for language. Qualifications Applicants must have completed all the requirements for the PhD by time of appointment, or they must expect to obtain the PhD within a year of joining the faculty as Instructor. Degree must be in linguistics, computer science, cognitive science, or a related field. Application Instructions Applicants should upload: a letter of application, a CV, a statement describing their research program, a statement of teaching interests (including a list of courses that the applicant would be prepared to teach), evidence of past teaching performance or teaching potential, three letters of recommendation, and three writing samples. The search committee will begin reviewing applications on November 15, 2025, and continue until the position is filled. Salary is competitive and commensurate with experience and qualifications. Position funding is subject to budget availability. For further information Prof. Kyle Mahowald, Search Committee Chair Email: kyle@utexas.edu If you apply for this position please say you saw it on Educaloxy

Department of Linguistics – The University of Texas at Austin
Start date: Fall 2026–27
Rank: Tenure-track Assistant Professor or Associate Professor with tenure

Description

The Department of Linguistics at The University of Texas at Austin invites applications for a position in computational linguistics to begin Fall of academic year 2026–27, at either the rank of tenure-track Assistant Professor or Associate Professor with tenure. We seek candidates whose work develops computational methods in any area of linguistics and specifically connects linguistics to artificial intelligence, with particular interest in candidates who can interface with any of our current major areas of research in syntax, semantics, pragmatics, sounds, psycholinguistics, cognitive science, language documentation, historical linguistics, sign language linguistics, or sociolinguistics.

Duties will include research, service, and teaching linguistics courses at all levels (lower- and upper-division undergraduate, and graduate), and training the next generation of researchers working in AI, natural language processing and machine learning, and computational methods for language.

Qualifications

Applicants must have completed all the requirements for the PhD by time of appointment, or they must expect to obtain the PhD within a year of joining the faculty as Instructor. Degree must be in linguistics, computer science, cognitive science, or a related field.

Application Instructions

Applicants should upload:

a letter of application,
a CV,
a statement describing their research program,
a statement of teaching interests (including a list of courses that the applicant would be prepared to teach),
evidence of past teaching performance or teaching potential,
three letters of recommendation,
and three writing samples.