FAU WAVE COMPETITION Apply Now!
Apply to receive seed funding for your innovative idea!
Open to graduate and undergraduate students.
Participants will develop their projects for a chance to win the $2,000 Dr. Eric H. Shaw FAU Wave Excellence in Innovation Award.
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This Job Announcement will remain open until a sufficient number of applications are received .
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Graduate Research Fellowship Program (GRFP).
The next application deadline for proposals in the mathematical sciences is October 20, 2023.
Please visit the GRFP website for more details and contact information.
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More Undergraduate and Graduate Student Opportunities
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This program is designed to provide a foundation for mathematical work and application of mathematics in scientific or technical fields and industry. It should normally take a fulltime student two years to complete. Five concentrations are offered: pure mathematics, applied analysis, biostatistics, cryptology, and information security, and financial mathematics. Students can enter an accelearated jointgraduate program in mathematics and electrical engineering, leading to an M.S. degree in mathematics and a Ph.D. in electrical engineering. See graduate level advisors for details.
In addition to meeting the University graduate admission requirements (including a score of at least 155 on the quantitative reasoning section of the GRE), applicants must have a bachelor's degree in mathematics or coursework that includes the equivalent of Introduction to Advanced Mathematics, Modern Algebra, and Probability and Statistics 1, as well as computer competency. Applicants who do not meet all of the requirements will still be considered for conditional admission.
A Bachelor's degree in Mathematics (or equivalent coursework) with at least 3.0 GPA (or equivalent), three letters of recommendation documenting the applicant's prior work in mathematics focusing on preparation and suitability for success in graduatelevel mathematics courses, a quantitative general GRE (revised) score of at least 155, and approval of the departmental graduate committee. In addition, it is recommended to include scores of the GRE subject test mathematics as part of the application package.
If your undergraduate major is not in Mathematics, see our Frequently Asked Questions page for a list of required prerequisite coursework.
Interested in the Master of Science in Teaching? Click here.
Click here for detailed application steps: application information.
To complete the M.S. degree in Mathematics, the candidate must complete at least 30 credits of graduate coursework and satisfy the following criteria in addition to University requirements:
To complete the M.S. degree in Mathematics, the candidate must complete at least 30 credit hours of graduate course work, and satisfy the following criteria in addition to University requirements:
1. Earn at least 24 credits in courses specified in a degree concentration, preapproved by the graduate advisor in mathematics, at least 15 credits of all credits applied to the degree must be at the 6000level.
2. If preapproved by the department graduate committee, up to 12 credits of FAU coursework from outside of the Department of Mathematical Sciences may count toward the degree.
3. Complete one of the following three capstone options below.
For information about the PHD, MS, and AMST programs contact
Prof. Hongwei Long, Graduate Director, at mathgraduate@fau.edu
Department of Mathematical Sciences
Florida Atlantic University
777 Glades RD
Boca Raton, FL 33431
For information about the Ph.D., MS, and AMST programs contact:
Prof. Hongwei Long, Graduate Director at mathgraduate@fau.edu
Department of Mathematical Sciences
Florida Atlantic University
777 Glades RD
Boca Raton, FL 33431
Capstone Options 

Thesis  6 credits 
MAT 6971  16 
Masters Thesis (may be taken over multiple terms) 

Internship  6 credits 

Internship in Applied Mathematics 
MAT 6941  16 
NonThesis, Non Internship  6 credits 

Select 6 credits of graduate courses at the 6000 level approved by the department and complete M.S. exam 
Pure Mathematics  24 credits 

Common Core Course 

Linear Algebra MAS 5145 3 cr 

Additional Core Courses  9 credits, select three of the following four courses 

lntroductory Analysis 1 MAA 5228 3 cr 

Introductory Analysis 2 MAA 5229 3 cr 

Introductory Abstract Algebra 1 MAS 5311 3 cr 

Introductory Abstract Algebra 2 MAS 5312 3 cr 

At least four elective courses  12 credits 

Select 12 credits at the 5000 or 6000 level from the Mathematical Sciences Department. A minimum of 9 credits must be taken at the 6000 level. 



Applied Analysis  24 credits 

Common Core Course 

Linear Algebra MAS 5145 3 cr 

Additional three core courses  9 credits 

Introductory Analysis 1 
MAA 5228 
Computational Mathematics 
MAD 6403 OR 
Numerical Analysis 
MAD 6704 
Ordinary Differential Equations 
MAP 6336 OR 
Partial Differential Equations 
MAP 6345 
At least four additional courses, 12 credits  
Introduction to Data Science 
CAP 5768 
Multivariable Analysis 
MAA 5105 
Introductory Analysis 2 
MAA 5229 
Real Analysis 
MAA 6306 
Complex Analysis 1 
MAA 6406 
Introduction to Functional Analysis 
MAA 6506 
Computational Mathematics 
MAD 6403 
Numerical Analysis 
MAD 6407 
Introduction to Dynamical Systems and Chaos 1 
MAP 6211 
Ordinary Differential Equations 
MAP 6336 
Partial Differential Equations 
MAP 6345 
General Topology 1 
MTG 6316 
Regression Analysis 
STA 6236 
Mathematical Statistics 
STA 6326 
Mathematical Probability 
STA 6444 
Applied Time Series Analysis 
STA 6857 
Biostatistics  24 credits 

Common Core Course 

Linear Algebra 
MAS 5145 3 cr 
Additional three core courses  9 credits 

Biostatistics 
STA 5195 
Mathematical Statistics 
STA 6326 
Mathematical Probability 
STA 6444 
At least five elective courses, 15 credits  
Introduction to Data Science 
CAP 5768 
Data Mining and Machine Learning 
CAP 6673 
Multivariable Analysis 
MAA 5105 
Numerical Analysis 
MAD 6407 
Statistical Computing 
STA 6106 
Survival Analysis 
STA 6177 
Biostatistics  Longitudinal Data Analysis 
STA 6197 
Applied Statistical Methods 
STA 6207 
Regression Analysis 
STA 6236 
Topics in Probability and Statistics (Stochastic Calculus) 
STA 6446 
Applied Time Series 
STA 6857 
Cryptology Track  24 credits 

Common Core Course 

Linear Algebra 
MASA 5145 3 cr 
Additional three core courses  9 credits 

Introduction to Cryptology and Information Security  MAD 5474 
Crypto Analysis  MAD 6478 
Coding Theory  MAD 6607 
Select three courses (9 credits)  
Introductory Abstract Algebra 1  MAS 5311 
Introductory Abstract Algebra 2  MAS 5312 
Introductory Analysis 1  MAA 5228 
Introductory Analysis 2  MAA 5229 
Mathematical Probability  STA 6444 
Mathematical Statistics  STA 6326 
At Least one Elective Course  
Algebraic Curves  MAS 6315 
Cryptography  MAD 6477 
Algebraic Number Theory  MAS 6215 
Mathematical Probability  STA 6444 
Mathematical Statistics  STA 6326 
Randomized Algorithms  COT 6446 
Analysis of Algorithm  COT 6405 
Secret Sharing Protocols  COT 6427 
Computer Networks  CNT 5008 
Information Theory  EEL 6532 
Computer Data Security  CIS 6370 
Special Topics  MAT 6933 
Computational Mathematics  MAD 6403 
Commutative Algebra  MAS 6333 
Topics in Algebra  MAS 6396 
Enumerative Combinatorics  MAD 6206 
Graph Theory  MAD 6307 
Distributed Systems Security  CIS 6375 
Cyber Security: Measurement and Data Analysis  CTS 6319 
Financial Mathematics  24 credits 

Common Core Coourse 

Linear Algebra 
MAS 5145 3 cr 
Additional six core courses  18 credits 

Introductory Analysis 1  MAA 5228 
Mathematical Statistics  STA 6326 
Mathematical Probability  STA 6444 
Applied Time Series Analysis  STA 6857 
Financial Mathematics 1  STA 6907 
Topics in Probability and Statistics (Stochastic Calculus)  STA 6446 
At Least One Elective course 

Regression Analysis  STA 6236 
Directed Independent Study  STA 6907 
Financial Management  FIN 6406 
Financial Markets  FIN 6236 
Portfolio Theory  FIN 6525 
Applied Statistical Methods  STA 6207 
Topics in Probability and Statistics  STA 6446 
Statistical Computing  STA 6106 
Introductory Analysis 2  MAA 5229 
Multivariable Analysis  MAA 5105 
Machine Learning and Data Mining  CAP 6673 
* As with all degree programs, the authoritative source for the degree requirements is the University Catalog that was in effect for the academic year in which the student entered the University. The information on this page does not supersede the Catalog.