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University and college computational linguistics openings worldwide
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Assistant Professor (tenure-track) - Departments of Philosophy and Linguistics, UC Davis
Assistant Professor in Linguistics
Chair Professor/ Professor/ Associate Professor / Assistant Professor (in Computational Linguistics or Natural Language Processing and in Experimental Linguistics)
Recruiting computational linguistics staff? Post a job and reach academic candidates directly.
Top computational linguists, NLP researchers, and language technologists are in high demand across both cutting-edge industry and leading academic institutions. Whether you specialize in machine translation, speech processing, or low-resource languages, exceptional opportunities exist to apply your expertise at scale.
Current Job Market Landscape
- Research scientist and applied scientist positions at major technology companies focusing on large language models
- Tenure-track and research faculty roles in university linguistics and computer science departments
- Specialist positions in government and defense organizations working on multilingual intelligence systems
- Roles in healthcare and accessibility companies developing clinical NLP and assistive technologies
Outstanding roles typically combine strong publication records, production-level coding ability, and experience translating research into deployed systems. Candidates who demonstrate both theoretical depth and practical impact consistently attract offers from the most prestigious employers.
AcademicJobs.com helps leading experts discover these selective positions by connecting top talent directly with universities and forward-thinking organizations seeking computational linguistics specialists. Professionals who regularly review curated listings stay ahead of emerging opportunities in both sectors.
To advance your career, maintain an active research profile, contribute to open-source NLP tools, and network at major conferences such as ACL, EMNLP, and NAACL. Tailoring applications to highlight measurable outcomes from previous projects significantly improves success rates.
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