Mathematics and Statistics with Interdisciplinary Applications (PhD)

Overview

The doctoral program in Mathematics and Statistics with Interdisciplinary Applications (MSIA) is designed to provide a strong mathematics and statistics background to support intense quantitative work in diverse disciplines. The curriculum will prepare scholars to work on problems at the intersection of mathematics, science, engineering, medicine, finance, computer science, and other quantitative disciplines. The program aims to be the most inclusive and broadly interdisciplinary in Texas.

Program Requirements for Students with a Bachelor’s Degree

Students admitted with a bachelor’s degree will complete a minimum of 72 hours to earn the PhD in MSIA as follows:

  1. Required Core Courses – 12 hours
  2. Prescribed Electives – 15 hours
  3. Interdisciplinary Courses – 9 hours
  4. Dissertation/Seminar/Interdisciplinary Courses – 36 hours

Program Requirements for Students with Master’s Degree

Students admitted with a master’s degree will complete a minimum of 57 hours to earn the PhD in MSIA as follows:

  1. Required Core Courses – 6 hours
  2. Prescribed Electives – 6 hours
  3. Interdisciplinary Courses – 9 hours
  4. Dissertation/Seminar/Interdisciplinary Courses – 36 hours

Milestone Requirements

  • Preliminary Exam – students must pass a preliminary exam to progress to the candidacy exam. Students with full-time status may take the preliminary exam no later than their 2nd year in the program, while students with part-time status may take the preliminary exam within 4 years after they complete at least 6 program courses (or 18 hours) in the program.
  • Candidacy Exam – students must pass a candidacy exam to progress into their dissertation.
  • Dissertation Defense – students must successfully defend their dissertation.

Admission Requirements

Undergraduate students with a degree in a relevant application area do not require an undergraduate degree in mathematics or statistics.

In addition to general requirements of admissions to the UTRGV Graduate College, the doctoral program in Mathematics and Statistics with Interdisciplinary Applications will also require:

  1. B.S. or B.A. in a STEM field or related field, with at least 3 advanced undergraduate courses in Mathematics from the following areas: Linear Algebra, Differential Equations Modern Algebra I, Real Analysis I, Probability and Statistics Complex Variables or earned a Master's degree in Mathematics or a related field from a regionally accredited institution in the United States or a recognized international equivalent in a similar or related field with at least 3 undergraduate classes as given above;
  2. TOEFL score of 79 or better for international students if the medium of instruction in their bachelors or master’s program was not English;
  3. GRE General Test is required and the GRE Subject test in Mathematics is recommended;
  4. Personal Statement;

  5. Curriculum Vita;

  6. Three letters of recommendation. 

The program will accept part-time students as well as transfer students from other graduate programs. Transfer of graduate credit based on policies set out by the UTRGV Graduate College.

Application for admission must be submitted prior to the published deadline. The application is available at www.utrgv.edu/gradapply.

Program Requirements for Students Entering with a Bachelor's Degree - 72 Hours

Core Courses - 12 Hours

Students may choose 12 hours in the core courses upon advisement. 

MATH 8330Advanced Linear Algebra

3

MATH 8331Abstract Algebra

3

MATH 8333Advanced Statistical Learning

3

MATH 8352Advanced Analysis I

3

MATH 8360Advanced Ordinary Differential Equations

3

MATH 8364Advanced Statistical Methods

3

MATH 8365Advanced Probability & Statistics

3

MATH 8375Advanced Numerical Analysis

3

Prescribed Electives - 15 Hours

This degree plan includes courses that appear in more than one section of the degree plan. Such courses can only be used to fulfill one requirement on the degree plan and credit hours will only applied once.

MATH 8323Representation Theory

3

MATH 8329Analytic Number Theory

3

MATH 8332Commutative Algebra

3

MATH 8334Machine Learning

3

MATH 8335Deep Learning

3

MATH 8336Introduction to Data Science

3

MATH 8337Information Theory

3

MATH 8338Mathematical Foundations of Statistical and Quantum Mechanics

3

MATH 8339Advanced Complex Analysis

3

MATH 8343Linear Models

3

MATH 8344Function Space Methods in System Theory

3

MATH 8346Hydrodynamic Stability

3

MATH 8347Turbulence

3

MATH 8348Survival Analysis

3

MATH 8349Loss Models

3

MATH 8350Actuarial Risk Theory

3

MATH 8351Nonlinear hyperbolic PDEs

3

MATH 8353Measure Theory

3

MATH 8361Advanced Partial Differential Equations

3

MATH 8362Advanced Fourier Analysis

3

MATH 8363Solitons and Integrable Models

3

MATH 8366Advanced Microlocal Analysis

3

MATH 8369Mathematical Methods in Applied Sciences

3

MATH 8367Advanced Functional Analysis

3

MATH 8371Differential Geometry

3

MATH 8374Applications of Differential Geometry

3

MATH 8376Numerical Methods for Differential Equations

3

MATH 8377Advanced Fluid Mechanics

3

MATH 8378Advanced Inverse Problems and Image Reconstruction

3

MATH 8379Advanced Stochastic Processes

3

MATH 8381Advanced Mathematical Statistics

3

MATH 8382Advanced Statistical Computing

3

MATH 8384Advanced Biostatistics

3

MATH 8385Advanced Cryptology & Codes

3

MATH 8387Advanced Mathematical Modeling

3

MATH 8388Advanced Discrete Mathematics and Combinatorics

3

MATH 8398Interdisciplinary Course

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Interdisciplinary Courses - 9 Hours

This degree plan includes courses that appear in more than one section of the degree plan. Such courses can only be used to fulfill one requirement on the degree plan and credit hours will only applied once.

Computational Mathematics and Computer/Electrical Engineering

MATH 8343Linear Models

3

MATH 8344Function Space Methods in System Theory

3

MATH 8378Advanced Inverse Problems and Image Reconstruction

3

MATH 8385Advanced Cryptology & Codes

3

MATH 8388Advanced Discrete Mathematics and Combinatorics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Mathematical Physics

MATH 8338Mathematical Foundations of Statistical and Quantum Mechanics

3

MATH 8351Nonlinear hyperbolic PDEs

3

MATH 8363Solitons and Integrable Models

3

MATH 8371Differential Geometry

3

MATH 8374Applications of Differential Geometry

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Statistics with Data Analytics and Medical Applications

MATH 8334Machine Learning

3

MATH 8335Deep Learning

3

MATH 8336Introduction to Data Science

3

MATH 8337Information Theory

3

MATH 8348Survival Analysis

3

MATH 8349Loss Models

3

MATH 8350Actuarial Risk Theory

3

MATH 8382Advanced Statistical Computing

3

MATH 8384Advanced Biostatistics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Mathematical Biology and Nonlinear Mechanics

MATH 8346Hydrodynamic Stability

3

MATH 8347Turbulence

3

MATH 8377Advanced Fluid Mechanics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Dissertation/Seminar/Interdisciplinary Course - 36 Hours

MATH 8398Interdisciplinary Course

3

MATH 9101Graduate Research Seminar

1

MATH 9901Dissertation I

9

MATH 9902Dissertation II

9

MATH 9101 must be taken 6 times. MATH 9901 must be taken twice. 

Total Credit Hours: 57-72

Program Requirements for Students with Master’s Degree - 57 Hours

Core Courses - 6 Hours

Students may choose 6 hours in the core courses upon advisement. 

MATH 8330Advanced Linear Algebra

3

MATH 8331Abstract Algebra

3

MATH 8333Advanced Statistical Learning

3

MATH 8352Advanced Analysis I

3

MATH 8360Advanced Ordinary Differential Equations

3

MATH 8364Advanced Statistical Methods

3

MATH 8365Advanced Probability & Statistics

3

MATH 8375Advanced Numerical Analysis

3

Prescribed Electives - 6 Hours

This degree plan includes courses that appear in more than one section of the degree plan. Such courses can only be used to fulfill one requirement on the degree plan and credit hours will only applied once.

MATH 8323Representation Theory

3

MATH 8329Analytic Number Theory

3

MATH 8332Commutative Algebra

3

MATH 8334Machine Learning

3

MATH 8335Deep Learning

3

MATH 8336Introduction to Data Science

3

MATH 8337Information Theory

3

MATH 8338Mathematical Foundations of Statistical and Quantum Mechanics

3

MATH 8339Advanced Complex Analysis

3

MATH 8343Linear Models

3

MATH 8344Function Space Methods in System Theory

3

MATH 8346Hydrodynamic Stability

3

MATH 8347Turbulence

3

MATH 8348Survival Analysis

3

MATH 8350Actuarial Risk Theory

3

MATH 8351Nonlinear hyperbolic PDEs

3

MATH 8353Measure Theory

3

MATH 8361Advanced Partial Differential Equations

3

MATH 8362Advanced Fourier Analysis

3

MATH 8363Solitons and Integrable Models

3

MATH 8366Advanced Microlocal Analysis

3

MATH 8367Advanced Functional Analysis

3

MATH 8369Mathematical Methods in Applied Sciences

3

MATH 8371Differential Geometry

3

MATH 8374Applications of Differential Geometry

3

MATH 8376Numerical Methods for Differential Equations

3

MATH 8377Advanced Fluid Mechanics

3

MATH 8378Advanced Inverse Problems and Image Reconstruction

3

MATH 8379Advanced Stochastic Processes

3

MATH 8381Advanced Mathematical Statistics

3

MATH 8382Advanced Statistical Computing

3

MATH 8384Advanced Biostatistics

3

MATH 8385Advanced Cryptology & Codes

3

MATH 8387Advanced Mathematical Modeling

3

MATH 8388Advanced Discrete Mathematics and Combinatorics

3

MATH 8398Interdisciplinary Course

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Interdisciplinary Courses - 9 Hours

This degree plan includes courses that appear in more than one section of the degree plan. Such courses can only be used to fulfill one requirement on the degree plan and credit hours will only applied once.

Computational Mathematics and Computer/Electrical Engineering

MATH 8343Linear Models

3

MATH 8344Function Space Methods in System Theory

3

MATH 8378Advanced Inverse Problems and Image Reconstruction

3

MATH 8385Advanced Cryptology & Codes

3

MATH 8388Advanced Discrete Mathematics and Combinatorics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Mathematical Physics

MATH 8338Mathematical Foundations of Statistical and Quantum Mechanics

3

MATH 8351Nonlinear hyperbolic PDEs

3

MATH 8363Solitons and Integrable Models

3

MATH 8371Differential Geometry

3

MATH 8374Applications of Differential Geometry

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Statistics with Data Analytics and Medical Applications

MATH 8334Machine Learning

3

MATH 8335Deep Learning

3

MATH 8336Introduction to Data Science

3

MATH 8337Information Theory

3

MATH 8348Survival Analysis

3

MATH 8349Loss Models

3

MATH 8350Actuarial Risk Theory

3

MATH 8382Advanced Statistical Computing

3

MATH 8384Advanced Biostatistics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Mathematical Biology and Nonlinear Mechanics

MATH 8346Hydrodynamic Stability

3

MATH 8347Turbulence

3

MATH 8377Advanced Fluid Mechanics

3

MATH 8399Advanced Topics in Mathematics and Statistics

3

Dissertation/Seminar/Interdisciplinary Course – 36 Hours

MATH 8398Interdisciplinary Course

3

MATH 9101Graduate Research Seminar

1

MATH 9901Dissertation I

9

MATH 9902Dissertation II

9

Students must take MATH 9101 6 times, and MATH 9901 twice. 

Total Credit Hours: 57-72