Job Details

Assistant Professor in Mathematical Finance

Position Number: 9801315
Location: Lubbock, United States
Position Type: Mathematics

Assistant Professor in Mathematical Finance

46007BR
Position DescriptionThe Department of Mathematics and Statistics in the College of Arts & Sciences at Texas Tech University invites applications for a nine-month, tenure-track assistant professor position in mathematical finance, beginning September 1, 2027.All prospective employees are encouraged to visit Work at Texas Tech to learn more about becoming a part of our campus community.

Position Description
The Department of Mathematics and Statistics in the College of Arts & Sciences at Texas Tech University invites applications for a nine-month, tenure-track assistant professor position in mathematical finance, beginning September 1, 2027. All prospective employees are encouraged to visit Work at Texas Tech to learn more about becoming a part of our campus community.

About the University
Founded in 1923, Texas Tech University began with a mission to serve the needs of West Texas, but its impact has always reached far beyond. Today, Texas Tech, located in Lubbock (pop. 300,000+), is home to a vibrant community of more than 42,000 students.Texas Tech's 1,800-acre campus showcases Spanish Renaissance architecture and is home to one of the country's largest public art collections. Its 13 colleges include a prestigious School of Law and a distinguished School of Veterinary Medicine. These programs equip students with the skills and knowledge needed to excel in their respective fields. Built on the values of West Texas - hard work, grit and authenticity - the university graduates students who are deeply engaged in service to their communities and well-positioned to succeed in the world. Texas Tech is committed to achieving research and scholarly accomplishments that compare favorably to the member institutions of the Association of American Universities (AAU). For more than 100 years, Texas Tech has been a premier destination for those seeking a world-class education and a unique, personalized experience as a member of the Red Raider family.

About the College
Founded in 1925 as one of the university's four original colleges, the College of Arts & Sciences comprises 15 departments and offers a wide variety of courses and programs in the humanities, social and behavioral sciences, mathematics, physical sciences, and natural sciences. The College enrolls more than 10,000 students, representing more than one-quarter of the overall Texas Tech University student population, while maintaining a 22:1 student-to-faculty ratio.

About the Department/School/Area
The Department of Mathematics and Statistics at Texas Tech is one of the largest departments on campus. It includes 43 tenured and tenure-track faculty lines, 6-8 postdoctoral scholars each year, and an annual average of 15 lecturers and instructors. As of Fall 2026, the Department enrolled 216 undergraduate majors and 117 graduate students, with 105 supported full-time as graduate part-time instructors, teaching assistants, or research assistants. Our faculty, postdocs, and graduate students engage in active research across a wide range of areas in mathematics and statistics. The Department is committed to sustaining a strong research profile while providing high-quality education. We are dedicated to our students' success and to advancing research that benefits our field and the broader community.

Major/Essential Functions
In line with TTU's strategic priorities to engage and empower a dynamic student body, enable innovative research and creative activities, and transform lives and communities through outreach and engaged scholarship, applicants should have experience working with a breadth of student populations at the undergraduate and/or graduate levels within individual or across the areas of teaching, research/creative activity, and service.
As a faculty member in the Department of Mathematics & Statistics, you will be expected to: * Establish an internationally visible and independent research program;* Teach undergraduate and graduate courses in mathematical finance and related areas;* Advise and supervise graduate students;* Pursue external research funding;* Engage in interdisciplinary collaboration; and* Contribute to departmental, college, university, and professional service. The search is broadly defined within mathematical finance and includes dynamic asset pricing, portfolio optimization, derivatives, financial econometrics, Lvy processes, heavy tails, stochastic and rough volatility, market microstructure, systemic risk, financial networks, artificial intelligence and machine learning in finance, foundation models, reinforcement learning, explainable AI, autonomous financial decision systems, climate finance, ESG, digital assets, decentralized finance, ambiguity-aware finance, and robust optimization.

Faculty Qualifications
Applicants must: 1. Hold a Ph.D. in mathematics, statistics, mathematical finance, financial engineering, quantitative finance, actuarial science, economics, or a closely related field by the anticipated start date. 2. Demonstrate strong research ability, as evidenced by scholarly publications, working papers, a well-defined research agenda, presentations, grants, or other appropriate metrics of research productivity and impact. 3. Demonstrate effective teaching ability, as evidenced by teaching experience, student evaluations, teaching-related materials, instructional innovations, or other appropriate metrics of teaching effectiveness.

Preferred Qualifications
Preference will be given to candidates who demonstrate: 1. Strengths in one or more of the following areas: mathematical, statistical, econometric, or computational methods 2. Evidence of interdisciplinary collaboration3. Experience or ability to mentoring graduate students4. Evidence of the ability to develop an externally funded research program

Duty Point
TTU Lubbock, main campus and affiliated facilities

To apply, visit workattexastech.com

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information or status as a protected veteran.