Assistant Professor of Statistics
Colorado School of Mines
United States

Position Details

Institution: Colorado School of Mines (Mines)
Department: Applied Mathematics and Statistics (AMS)
Position Title: Assistant Professor, Data Science & Statistics
Rank: Tenure-track, Assistant Professor
Location: Golden, Colorado
Start Date: August 2026
Application Priority Deadline: March 1, 2026 (applications accepted until filled)
Salary Range: $98,500 – $111,000


Position Overview

The Department of Applied Mathematics and Statistics at Mines seeks a tenure-track Assistant Professor with expertise in Data Science and Statistics, particularly in the application to spatial and space-time data relevant to geosciences, energy systems, environment, or critical minerals.

Primary Responsibilities:

  • Develop and maintain an externally funded research program in Data Science and Statistics.

  • Conduct high-quality teaching in undergraduate and graduate courses, bridging theory and practical applications.

  • Supervise and mentor undergraduate and graduate students in coursework and research.

  • Contribute to the department, university, and professional community through service, leadership, and committee work.

Preferred Expertise:

  • Application of data science/statistics to spatial or space-time data.

  • Experience addressing scientific problems in geosciences, environment, or energy systems.

  • Evidence of or potential for research leadership, engagement in professional societies, and securing external funding.


Minimum Qualifications

  • PhD in Data Science, Statistics, or a closely related field.

  • Record of peer-reviewed publications in statistics or data science.

  • Research experience in academic, lab, or industry environments.

  • Demonstrated potential for excellence in research, teaching, and mentorship.

  • Strong communication and interpersonal skills.

  • Potential to establish a funded and impactful research program.


Department & University Overview

  • Students: ~6,400 undergraduates; ~1,900 graduate students.

  • Research funding: ~$106M (FY2024).

  • AMS Department: 23 faculty; offers B.S., M.S., Ph.D. programs; focus on computational applied math, statistics, and data science.

  • Mines emphasizes interdisciplinary collaboration with government labs (NREL, NIST, NCAR, NOAA), industry, and other universities.

Departmental focus areas:

  • Computational and applied mathematics, statistics, and data science.

  • Modeling and analysis of large-scale and complex datasets.

  • Interdisciplinary collaboration and applied problem-solving.

Website: AMS Department


Application Instructions

Applicants must submit the following (online application only):

  1. Curriculum Vitae

  2. Statement of Research (≤4 pages)

  3. Statement of Teaching (≤2 pages)

  4. Cover Letter expressing interest

  5. Up to three representative research papers (PDFs)

Research Statement: Should describe past research, connections to Mines, societal impact, and plans for future research/funding.

Teaching Statement: Should outline in-person, hands-on, project-based pedagogy, and experience with online education.

References: Contact information for references will be requested; references contacted later in process.

Submit application: Mines online portal.


Benefits & Total Rewards

  • Flexible health and dental options

  • Fully vested retirement plan with 12% employer contribution from day one

  • Tuition benefits (6 credits/year for employees; 50% discount for dependents)

  • On-campus daycare center

  • Free RTD Ecopass for local transit

  • Access to Recreation Center and Outdoor Recreation Center

  • Athletics tickets and employee discount programs


Equal Opportunity & Accommodation

  • Mines is an equal opportunity employer. No discrimination based on age, gender, race, religion, disability, veteran status, or other protected categories.

  • Reasonable accommodations available under the ADA/ADAAA.

  • Background check required.

Contact for questions: Soutir Bandyopadhyay, AMS search committee chair –


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