Assistant Professor in Mathematical Finance – Texas Tech University

Assistant Professor in Mathematical Finance – Texas Tech University

• Institution: Texas Tech University

• Academic Unit / Department: Department of Mathematics and Statistics, College of Arts & Sciences

• Job Reference / Requisition ID: 46007BR

• Appointment Type: Full-Time, Tenure-Track, 9-Month

• Academic Rank / Level: Assistant Professor

• Salary / Remuneration: Compensation commensurate with qualifications, departmental budget, and institutional pay plan

• Location: Lubbock, Texas, USA

• Application Deadline: December 15, 2026

• Anticipated Start Date: September 1, 2027

📋 Overview of Role

Texas Tech University invites applications for a nine-month, tenure-track Assistant Professor position in Mathematical Finance within the Department of Mathematics and Statistics. The successful candidate will establish an internationally visible research program, teach undergraduate and graduate courses, mentor graduate students, and contribute to interdisciplinary research and professional service.

The search encompasses a broad range of mathematical finance and quantitative finance, including asset pricing, portfolio optimization, financial econometrics, stochastic and rough volatility, financial networks, AI and machine learning in finance, climate finance, ESG, digital assets, decentralized finance, and robust optimization.

🎯 Key Responsibilities & Teaching Scope

• Teach undergraduate and graduate courses in mathematical finance and related areas.

• Establish and maintain an independent, internationally visible research program.

• Pursue external research funding and develop a sustainable funded research agenda.

• Advise and supervise graduate students.

• Engage in interdisciplinary research and collaboration.

• Contribute to departmental, college, university, and professional service.

• Conduct research in areas such as dynamic asset pricing, derivatives, portfolio optimization, financial econometrics, stochastic processes, volatility modeling, systemic risk, financial networks, AI/ML in finance, foundation models, reinforcement learning, climate finance, ESG, digital assets, DeFi, and robust optimization.

🎓 Qualifications & Candidate Profile

• Required Education: Ph.D. in mathematics, statistics, mathematical finance, financial engineering, quantitative finance, actuarial science, economics, or a closely related field by September 1, 2027.

• Research Profile: Strong research ability demonstrated through scholarly publications, working papers, research agenda, presentations, grants, or other evidence of research impact.

• Teaching Profile: Demonstrated effective teaching ability through teaching experience, student evaluations, teaching materials, or instructional innovations.

• Preferred Expertise: Mathematical, statistical, econometric, or computational methods.

• Preferred Experience: Interdisciplinary research collaboration and graduate student mentoring.

• Research Funding: Preference for candidates demonstrating the ability to develop an externally funded research program.

💼 Remuneration & Benefits

• Salary: Compensation is determined according to the candidate's qualifications, departmental budgetary guidelines, and Texas Tech University's institutional pay plan.

• Pay Basis: Monthly

• Travel: Up to 25% may be required.

• Grant Funded: No

• Salary Grade: 800

• Work Location: TTU Lubbock main campus and affiliated facilities.

📄 Application Checklist & Required Documents

1. Cover Letter

2. Curriculum Vitae (CV)

3. Research Statement

4. Teaching Statement

5. Contact Information for at least three professional references

6. Reference letters will be requested directly from references for semifinalists.

📬 Application Process

• 🔗 Application Link: Apply now

• 📧 Search Committee Chair: Dr. Alex Trindade — alex.trindade@ttu.edu

• 📧 Application Assistance: Texas Tech University Human Resources, Talent Acquisition — hrs.recruiting@ttu.edu

• ☎️ HR Phone: 806-742-3851

• 📅 Deadline: December 15, 2026

• 📅 Anticipated Start Date: September 1, 2027

🌐 Official Website / Domain Link: https://www.ttu.edu/