Mathematics and Statistics with Interdisciplinary Applications (PhD)

CIP Code

27.0101.00

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.

Admission requirements

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

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

  • Comprehensive Exam – Students will be required to pass the Comprehensive Exam by the end of the second year of graduate study. Through close advising, the first-year coursework will be tailored to a student’s background and similarly, the comprehensive exam will also be tailored to each student’s coursework, background, and research goals. Depending on their background, some students may take the comprehensive exam during their first year while others will take it in the 2nd year. The comprehensive exam will consist of written exams covering topics in each of the eight subjects covered in the core courses. A separate exam in each subject will be offered at the beginning of the fall, spring, and summer semesters. To advance, the student must pass at least three subject exams. An “A” grade in one of the core courses will exempt the student from at most one exam. Students may take each exam up to three times but must pass all the required exams to remain in the program.
  • Candidacy Exam – students must pass a candidacy exam to progress into their dissertation.
  • Dissertation Defense – students must successfully defend their dissertation.

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. 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.

Program Requirements

Required Core Courses - 6 or 12 Hours

MATH 6330Linear Algebra

3

MATH 6331Algebra I

3

MATH 6333Statistical Learning

3

MATH 6352Analysis I

3

MATH 6360Ordinary Differential Equations

3

MATH 6364Statistical Methods

3

MATH 6365Probability and Statistics

3

MATH 6375Numerical Analysis

3

Prescribed Electives - 6 or 15 Hours

MATH 8323Group Theory

3

MATH 8329Number Theory

3

MATH 8332Algebra II

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 8339Complex Theory

3

MATH 8353Analysis II

3

MATH 8361Partial Differential Equations

3

MATH 8362Fourier Analysis

3

MATH 8363Integrable Systems

3

MATH 8366Micro-Local Analysis

3

MATH 8367Functional Analysis

3

MATH 8369Mathematical Methods

3

MATH 8371Differential Geometry

3

MATH 8376Numerical Methods for Partial Differential Equations

3

MATH 8379Stochastic Processes

3

MATH 8381Mathematical Statistics

3

MATH 8387Mathematical Modeling

3

MATH 8388Discrete Mathematics

3

Interdisciplinary Courses - 9 Hours

Computational Mathematics and Computer/Electrical Engineering

CSCI 6323Design and Analysis of Algorithms

3

CSCI 6356Parallel Computing

3

ELEE 6315Applied Electromagnetics

3

ELEE 6345Digital Signal Processing I

3

ELEE 6347Image Processing

3

MATH 8378Inverse Problem and Image Reconstruction

3

MATH 8385Cryptology & Codes

3

MATH 8388Discrete Mathematics

3

MATH 8343Linear Models

3

MATH 8344Function Space Methods in System Theory

3

Mathematical Biology and Nonlinear Mechanics

BIOL 6320Vector Biology

3

BIOL 5421Biotechnology

4

BIOL 6400Neuroscience

4

MECE 6372Viscous Flow I

3

MECE 6375Engineering Acoustics

3

MECE 6379Gas Dynamics

3

MATH 8346Hydrodynamic Stability

3

MATH 8347Turbulence

3

MATH 8377Mathematical Fluid Mechanics

3

Data Analytics and Medical Applications
CSCI 6355Bioinformatics

3

CSCI 6366Data Mining and Warehousing

3

STAT 5301Statistical Data Analysis

3

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 8382Statistical Computing

3

MATH 8384Biostatistics

3

Mathematical Physics
PHYS 5340Quantum Mechanics I

3

PHYS 5392Gravitational Wave Astronomy

3

PHYS 5393Introduction to General Relativity and Gravitation

3

PHYS 6352Computational Physics

3

MATH 8338Mathematical Foundations of Statistical and Quantum Mechanics

3

MATH 8371Differential Geometry

3

MATH 8363Integrable Systems

3

MATH 8351Nonlinear hyperbolic PDEs

3

MATH 8374Applications of Differential Geometry

3

Dissertation/Seminar/Interdisciplinary Course - 36 Hours

MATH 9901Dissertation I

9

MATH 9901Dissertation I

9

MATH 9902Dissertation II

9

MATH 9101Graduate Research Seminar

1

MATH 9101Graduate Research Seminar

1

MATH 9101Graduate Research Seminar

1

MATH 9101Graduate Research Seminar

1

MATH 9101Graduate Research Seminar

1

MATH 9101Graduate Research Seminar

1

MATH 8398Interdisciplinary Course

3

Total Credit Hours: 57