Program Details

PhD Requirements

The PhD requires a minimum of 72 graduate credit hours that include core and elective course work and a thesis. Coursework is valid for nine years toward a PhD degree; any exceptions must be approved by the director of the ORwE program and the student’s advisor.

PhD: Degree Requirements


  1. Foundational Programming Concepts & Design (CSCI200)
  2. Data Structures and Algorithms (CSCI220)

Students entering in the fall semester must have completed the Foundational Programming Concepts & Design (CSCI200) prerequisite or equivalent. Students may take CSCI220 during their first semester of study. Students will only be allowed to enter in the spring semester if they have developed a course program such that they are able to take the qualifying exam within 3 semesters.

Course work

  • 24 credits of core courses
  • 12 credits of elective courses
  • 12 additional credits

Research credits

At least 24 research credits are required. The student’s faculty advisor and the doctoral thesis committee must approve the student’s program of study and the topic for the thesis.

Qualifying Examination Process and Thesis Proposal

Upon completion of the core course work, students must pass a written qualifying examination and complete a qualifying research project to become a candidate for the PhD ORwE degree. The proposal defense should be completed within ten months of passing the qualifying exam.

Transfer Credits

Students may transfer up to 24 hours of graduate-level course work from other institutions toward the PhD degree subject to the restriction that those courses must not have been used as credit toward a Bachelors degree. The student must have achieved a grade of B or better in all graduate transfer courses and the transfer must be approved by the student’s Doctoral Thesis Committee and the Director of the ORwE program.

Unsatisfactory Progress

In addition to the institutional guidelines as described in the bulletin, we impose the following criteria regarding unsatisfactory progress: Unsatisfactory progress will be assigned to any full-time student who does not pass the core courses within the first three semesters of their study. Unsatisfactory progress will also be assigned to any student who does not complete requirements as specified in his or her admission letter. Any exceptions to the criteria regarding unsatisfactory progress must be approved by the ORwE committee. Part-time students develop an approved course plan with their advisor.

PhD Curriculum

Core Courses (24 credits)

Elective Courses (12 credits)

Students are required to take 4 courses from the electives list:

  • CSCI555 Game Theory and Networks
  • CSCI562 Applied Algorithms and Data Structures
  • CSCI598 Network Science and Graph Analytics
  • EBGN509 Mathematical Economics
  • EBGN528 Industrial Systems Simulation (or MATH542/CSCI542 Simulation)
  • EBGN560 Decision Analytics
  • EBGN575 Advanced Mining and Energy Asset Valuation
  • EENG517 Theory and Design of Advanced Control Systems
  • EENG521 Numerical Optimization
  • MATH424 Introduction to Applied Statistics
  • MATH532 Spatial Statistics
  • MATH537 Multivariate Analysis
  • MATH560 Intro to Key Statistical Learning Methods
  • MATH561 Intro to Key Statistical Learning Methods II
  • MATH582 Statistics Practicum
  • MEGN592 Risk and Reliability Engineering Analysis and Design
  • MNGN536 Operations Research Techniques in the Mineral Industry
  • MNGN538 Geostatistical Ore Reserve Estimation
  • MTGN450/MLGN550 Statistical Process Control and Design of Experiments
  • ORWE686 Advanced Linear Optimization
  • ORWE688 Advanced Integer Optimization
  • 5XX/6XX Special Topics (Requires approval of the advisor and ORwE program director)

Program codes: CSCI: Computer Science, EBGN: Economics and Business, MATH: Applied Mathematics and Statistics, MEGN: Mechanical Engineering, MNGN: Mining Engineering, MTGN: Metallurgical and Materials Engineering.


Master of Science, Non-Thesis (MSNT) Requirements

The MSNT requires 30 credit hours, 18 of which are core courses and the other 12 of which are ORwE courses not taken as core courses.

MSNT: Degree Requirements

All Masters students are required to take a set of 6 core courses (18 hours):

  • MATH424 Introduction to Applied Statistics
    or EBGN528 Simulation
  • MATH530 Introduction to Statistical Methods
  • ORWE586 Linear Optimization
    or ORWE585 Network Models
  • MATH538/EBGN526 Stochastic Models (course may be substituted with MATH 4XX Computational Linear Algebra)
  • ORWE587 Nonlinear Optimization
    or EENG511 Convex Optimization And Its Engineering Applications
    or ORWE588 Integer Optimization
  • MEGN502 Advanced Engineering Analysis
    or CSCI406 Algorithms
    or CEEN405 Numerical Methods for Engineers
    or CEEN505 Numerical Methods for Engineers

The remaining 12 hours of coursework can be completed with any ORwE-labeled course not taken as core. Or, specialty tracks can be added. See the ORwE program page in the Mines Catalog for examples of specialty tracks and the applicable courses within each.

Students who do not wish to specialize in a track mentioned in the table below and do not wish to complete 12 additional hours of ORwE-labeled coursework can “mix and match” from the ORwE coursework and coursework listed in the tables on the ORwE program page in the Mines Catalog in consultation with and approval from their academic advisers.