Assistant Professor

NMSU; New Mexico; On-site; USD 86,000 - 106,000; Full time

Job summary

NMSU in Las Cruces seeks an Assistant Professor in Applied Statistics within the Business College. The candidate will teach undergraduate and graduate statistics courses, conduct peer-reviewed research, and advise graduate students. The role emphasizes service to the department and collaboration across programs.

Applicants should hold a PhD in Statistics or closely related field. The position is tenure-track with expected contributions to teaching, research, and grant development in a dynamic

Job description

Department Contact:Yu-Feng Lee, [phone], [e-mail]

Internal or External Search:External - Open to all applicants

Advertising Summary:The Applied Statistics Program offers MS and PhD degrees in Applied Statistics and a variety of courses at the undergraduate and graduate levels. The MS program offers courses in both the theory and the application of statistics. The recently launched PhD program is designed to provide graduates with the knowledge of a range of applied statistical methods, both basic and advanced, sufficient to independently solve complex data problems in a collaborative research environment, to teach these methods at the undergraduate level, and to contribute substantively to the development of grant proposals and applied research publications.

Position Details

PositionTitle: Assistant Professor

College/Division: Business College

Department: 340300-ECONOMICS AND INTERNATIONAL BUSINES

Location: Las Cruces

Offsite Location (if applicable):

Target Hourly/Salary Rate: 96,000

Appointment Full-time Equivalency: 1.0

FLSA Status:Exempt

Bargaining Unit Announcement: This is a bargaining unit position with the National Education Association (NEA).

Contingent Upon Funding:Not Applicable

Standard Work Schedule:Standard (M-F, 8-5)

If Not a Standard Work Schedule:

Job Duties and Responsibilities: The Department of Economics, Applied Statistics, and International Business seeks to fill a 9-month tenure-track position in Applied Statistics at the rank of assistant professor. The newly hired Assistant Professor is expected to provide high quality teaching, conduct peer-reviewed research, advise graduate students, and participate in typical university, college, and departmental activities. Faculty teach applied statistics courses at the undergraduate level; at the master’s level to students majoring in Applied Statistics and to graduate students from other fields; and at the doctoral level to students pursuing a PhD in Applied Statistics. Peer-reviewed research can be conducted individually or collaboratively, depending on the interests of the faculty member. Faculty advise graduate students pursuing an Applied Statistics degree or earning the minor in Applied Statistics.

Qualifications

Required Education and Experience: A PhD in Statistics or a closely related field is required prior to the date of hire. We seek candidates with the potential to teach undergraduate and graduate Statistics courses to students from diverse backgrounds and fields of study. All areas of methodological and applied research in statistics will be fully considered; candidates with expertise in areas such as Bayesian methods, computational statistics, causal inferences, AI/ML, Econometrics, and Business Analytics are especially encouraged to apply.

Applicants must submit the following materials:

• Cover letter
• Curriculum vitae
• Transcripts
• A statement describing teaching experience and philosophy
• A research statement describing current and future research work
• Contact information for at least three referees (referees may be contacted at a later date)
• Publication preprints (optional)

Working Conditions and Physical Effort

Environment: Work is normally performed in a typical interior/office work environment.

Physical Effort: No or very limited physical effort required.

Lifting Requirements: Requires handling of average-weight objects up to 10 pounds or some standing or walking.

Risk: No or very limited exposure to physical risk.