Doctor of Philosophy in Mathematics and Statistics
Ph.D. with a concentration in Bioinformatics, Biostatistics, or Mathematics
For the details on how to apply, please follow the link
1. Entrance Requirements: For entry to the Ph.D. program regardless of concentration students must have a baccalaureate degree in mathematics, statistics, or a related field with a grade point average of 3.0 out of 4.0. Students with a grade point average of 2.75 will be considered for conditional admission. Students must provide three letters of reference, recent GRE scores, and a statement describing study plans. Applicants from non-English speaking countries must achieve a satisfactory score on the Test of English as a Foreign Language (TOEFL).
Students must have completed courses in mathematics equivalent to the following with a grade of B or higher:
Math 4435/6435: Linear Algebra
Math 4661/6661: Analysis I
Math 4662/6662: Analysis II
2. Common courses: Each of the concentrations requires 54 hours of coursework and 30 hours of dissertation research. Students must take four of the five following common core courses ( 12 credit hours):
Ma th 8110: Real Analysis I
Math 8200: Advanced Matrix Analysis
Stat 8600: Probability Theory
Stat 8561: Linear Statistical Analysis I
Math 9116: Teaching College Math Sciences
3. Additional required and elective courses:
The following describe requirements that are specific to each concentration.
Bioinformatics
The following courses are required (12 credit hours):
Math 8515: Mathematical Neuroscience
Math 8510: Applied Mathematics
Stat 8050: Statistics for Bioinformatics
Stat 8581: Statistical Theory I
Students must take at least 9 credit hours selected from the list below (9 credit hours).
Math 6010: Mathematical Biology
Math 6275: Applied Dynamical Systems
Math 8520: Applied Combinatorics & Graph Theory
Math 8540: Advanced Topics in ODEs and Dynamical Systems
Stat 8561: Linear Statistical Analysis I
Stat 8582: Statistical Theory II
Stat 8610: Time Series Analysis
Students must take at least 21 credit hours that should be selected from other graduate level courses in the Department of Mathematics and Statistics and courses from other departments listed below. The total number of required hours of coursework is 54; if Stat 8561 is taken as part of the core and used to also satisfy the 9 required hours above, a student must take additional coursework in Mathematics and Statistics or from the list below.
Biol 6564: Advanced Genetics
Biol 7900: Genetics
Biol 8220: Molecular Cell Biology
Biol 8010: Neurobiology I, Cellular Neurobiology
Biol 8020: Neurobiology II, Integrative Neurobiology
Biol 8610: Physiology and Genetics of Prokaryotes
Biol 8410: Advanced Microbiology
Chem 6450: Molecular Modeling Methods
Chem 8360: Protein Structure and Function
Chem 8370: Nucleic Acid Structure and Function
Chem 8510: Biophysical Chemistry
Chem 8620: Advanced Topics in Biochemistry
CSc 8630: Bioinformatics
CSc 8711: Database on the web
CSc 8510: Theory of Computation
CSc 8830: Mathematical Models and Simulation
Biostatistics
The following two courses should be included if they are not selected in the core courses:
Stat 8600: Probability Theory
Stat 8561: Linear Statistical Analysis I
The following courses (27 credit hours) are required:
Stat 8440: Survival Analysis
Stat 8540: Advance Methodologies in Biostatistics
Stat 8562: Linear Statistical Analysis II
Stat 8581 & Stat 8582: Statistical Theory I & II
Stat 8678: SAS programming
Stat 8700: Categorical Data Analysis
Stat 8800: Statistical Consulting
Ph 7011: Epidemiology for Public Health
At least 15 credit hours should be selected from other graduate level courses in the Department of Mathematics and Statistics and courses from other departments listed as follows:
Biol 6564: Advanced Genetics
Biol 7800: Molecular Cell Biology
Biol 7900: Genetics
Biol 8010: Neurobiology I: Cellular
Biol 8220: Molecular Cell Biology
Biol 8630: Bioinformatics
CSc 6520: Design & Analysis-Algorithms
CSc 6810: Artificial Intelligence
CSc 8220: Advanced Computer Networks
CSc 8221: Optical/Wireless Networks
CSc 8530: Parallel Algorithms
CSc 8710: Deductv Databs/Logic Prog
CSc 8711: Databases and the Web
CSc 8810: Computational Intelligence
CSc 8830: Math Models & Simulation
Ph 7010: Found of Pub Hlth Admin & Pol
Ph 7011: Epidemiology
Ph 7170: Research in Health Policy
Ph 7270: Int Epidemiologic Methods
Ph 7300: Urban Health
Ph 7530: Prevn Effect & Econ Evaluation
Mathematics
The mathematics concentration requires that a student choose three of the following five areas as subjects for the qualifying exam and take the two required courses for the topic if they were not taken as part of the common core. The qualifying exam is comprised of three separate written exams on each of the three chosen areas. The exam is administered by the department.
Analysis: Math 8110 Real Analysis I and Math 8120 Real Analysis II
Matrix Theory: Math 8200 Advanced Matrix Analysis and Math 8620 Numerical Linear Algebra
Algebra: Math 8220 Abstract Algebra and Math 8221 Abstract Algebra II
Discrete Mathematics: Math 8420 Advanced Graph Theory and Math 8440 Combinatorics
Applied Mathematics: Math 8150 Applied Mathematics and Math 8610 Advanced Numerical Analysis
For breadth and specialization a student following the concentration in mathematics will take at least 8 additional courses (24 hours) chosen from the following. At least three but no more than four should be 8000 level courses within the student's chosen area of specialization. Students are not permitted to take 6000 level courses in an area in which they have taken a qualifying exam. Topics courses can be taken more than once if the topic is different. The total number of hours of coursework should not be less than 54 hours. If there is overlap between courses taken for the qualifying exam and the common core then additional courses from the following list should be taken to meet the requirement for 54 hours. Two of the 8000 level courses within the student's specialty will be chosen by the student as the basis for the candidacy exam.
Analysis:
Math 6250: Complex Analysis
Math 6258: Vector Calculus
Math 6265: Partial Differential Equations
Math 6661: Analysis I
Math 6662: Analysis II
Math 8310: Theory of Functions of a Complex Variable
Matrix Theory:
Math 6435: Linear Algebra
Math 8210: Topics in Applied Matrix Analysis
Math 8201: Combinatorial Matrix Theory
Algebra:
Math 6441: Modern Algebra I
Math 6442: Modern Algebra II
Math 6444: Polynomials
Math 6450: Theory of Numbers
Math 6455: Error Correcting Codes
Math 6460: Cryptography
Math 8230: Topics in Algebra
Math 8240: Introduction to Commutative Algebra and Algebraic Geometry
Math 8250: Commutative Ring Theory
Discrete Mathematics:
Math 6420: Graph Theory
Math 8520: Applied Combinatorics and Graph Theory
Math 8450: Probabilistic Method in Combinatorics
Applied Mathematics:
Math 6010: Mathematical Biology
Math 6211: Optimization
Math 6253: Introduction to Operations Research
Math 6275: Applied Dynamical Systems
Math 6610: Numerical Analysis I
Math 6620: Numerical Analysis II
Math 6650: Inverse and Ill-posed Problems
Math 6671: Transforms in Applied Mathematics
Math 8530: Topics in Applied Mathematics
Math 8540: Advanced Topics in Ordinary Differential Equations and Dynamical Systems
In addition to the above courses, students may to satisfy the breadth requirement take the following.
Math 6381: General Topology
Math 8515: Mathematical Neuroscience