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Machine Learning Professor Jobs in Texas (NOW HIRING)

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Machine Learning Professor information

What are the key skills and qualifications needed to thrive as a Machine Learning Professor, and why are they important?

To thrive as a Machine Learning Professor, you need deep expertise in machine learning algorithms, mathematics, and data science, typically supported by a Ph.D. in computer science or a related field. Familiarity with programming languages like Python and R, as well as tools such as TensorFlow, PyTorch, and academic research platforms, is essential. Exceptional communication, mentorship abilities, and enthusiasm for teaching help inspire and guide students and peers. These skills ensure effective research output, high-quality teaching, and the development of future leaders in the field.

How does a Machine Learning Professor typically balance research, teaching, and mentorship responsibilities?

Machine Learning Professors usually split their time between conducting original research, teaching undergraduate and graduate courses, and mentoring students. Balancing these responsibilities can be challenging, particularly when managing multiple research projects and supervising student theses. Professors often collaborate with industry partners and other academic departments, which enhances research opportunities but also adds to their workload. Effective time management and prioritization are key to thriving in this dynamic environment, and universities often provide some flexibility in teaching loads or research support to help maintain this balance.

What does a Machine Learning Professor do?

A Machine Learning Professor teaches university-level courses on machine learning, data science, and related topics. They conduct original research in the field, often publishing their findings in academic journals and presenting at conferences. In addition to lecturing, they mentor students, supervise theses or dissertations, and may collaborate with industry partners on research projects. Their work helps advance the understanding and applications of machine learning.
Machine Learning Professor jobs near you
Infographic showing various Machine Learning Professor job openings in Texas as of June 2026, with employment types broken down into 3% Internship, 65% Full Time, 13% Part Time, 3% Temporary, 13% Contract, and 3% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Assistant or Associate Professor - Computational Linguistics

The University of Texas at Austin

Austin, TX • On-site

Full-time

Posted 12 days ago

University Of Texas at Austin rating

8.1

Company rating: 8.1 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

131st of 535 rated colleges and universities

Job description

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, please contact:
Prof. Kyle Mahowald, Search Committee Chair
Email:kyle@utexas.edu

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