- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Bachelor's Degree Entry
Complete all courses and requirements listed below unless otherwise indicated.
Milestones
Four qualifying examinations
Annual review
Teaching requirement
Doctoral candidacy
Dissertation committee
Dissertation proposal
Progress report and presentation
Dissertation defense
Prerequisites
| Code | Title | Hours |
|---|---|---|
| Algebra and Analysis | ||
| Complete 0–8 semester hours from the following: | 0-8 | |
| Analysis 1: Functions of One Variable | ||
| Algebra 1 | ||
Advanced Coursework
| Code | Title | Hours |
|---|---|---|
| Complete 32 semester hours from the advanced coursework list. Only two readings and three topics courses are allowed. | 32 | |
Tracks
Complete one of the following three tracks:
Dissertation
| Code | Title | Hours |
|---|---|---|
| Dissertation Term 1 | ||
| Dissertation Term 2 |
Program Credit/GPA Requirements
48–56 total semester hours required
Minimum 3.000 GPA required
Pure Track
| Code | Title | Hours |
|---|---|---|
| Analysis | ||
| MATH 5102 | Analysis 2: Functions of Several Variables | 4 |
| Algebra | ||
| MATH 5112 | Algebra 2 | 4 |
| Foundational Courses | ||
| Complete up to 8 semester hours from the following: | 0-8 | |
| Topology 1 | ||
| Geometry 1 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Probability 1 | ||
Discrete Track
| Code | Title | Hours |
|---|---|---|
| Algebra | ||
| MATH 5112 | Algebra 2 | 4 |
| Probability | ||
| MATH 7241 | Probability 1 | 4 |
| Foundational Courses | ||
| Complete up to 8 semester hours from the following: | 0-8 | |
| Analysis 2: Functions of Several Variables | ||
| Algebra 1 | ||
| Algebra 2 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Mathematical Statistics | ||
Probability and Statistics Track
| Code | Title | Hours |
|---|---|---|
| Analysis | ||
| Complete 4 semester hours from the following: | 4 | |
| Analysis 2: Functions of Several Variables | ||
| Numerical Analysis 1 | ||
| Probability | ||
| MATH 7241 | Probability 1 | 4 |
| or MATH 7342 | Mathematical Statistics | |
| Foundational Courses | ||
| Complete up to 8 semester hours from the following: | 8 | |
| Analysis 2: Functions of Several Variables | ||
| Algebra 2 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Probability 1 | ||
| Mathematical Statistics | ||
Advanced Coursework List
| Code | Title | Hours |
|---|---|---|
| Numerical Analysis 2 | ||
| Topology 2 | ||
| Riemannian Optimization | ||
| Graph Theory | ||
| Optimization and Complexity | ||
| Machine Learning and Statistical Learning Theory 1 | ||
| Functional Analysis | ||
MATH 7302 | ||
MATH 7303 | ||
| Commutative Algebra | ||
| Algebraic Number Theory | ||
MATH 7316 | ||
| Modern Representation Theory | ||
| Modern Algebraic Geometry | ||
| Topology 3 | ||
| Machine Learning and Statistical Learning Theory 2 | ||
| Probability 2 | ||
| Applied Statistics | ||
| Regression, ANOVA, and Design | ||
MATH 7346 to MATH 7361 | ||
| Morse Theory | ||
MATH 7374 | ||
MATH 7976 to MATH 8986 | ||
| Research | ||
| Topics | ||
| Only three topics courses are allowed. | ||
| Topics in Algebra | ||
| Topics in Algebraic Geometry | ||
| Topics in Representation Theory | ||
| Topics in Topology | ||
| Topics in Combinatorics | ||
| Topics in Probability | ||
| Readings | ||
| Only two readings courses are allowed. | ||
| Readings in Topology | ||
| Readings in Graph Theory | ||
| Readings in Algebra | ||
| Readings in Algebraic Geometry | ||
| Readings in Discrete Geometry | ||
| Readings in Probability and Statistics | ||
| Readings in Geometry | ||
- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Course Requirements
Advanced students who enter the PhD program with a master's degree (or equivalent) will be allowed to place out of some (possibly all) of the six basic-level courses; the graduate coordinator together with the first-year graduate advisor will determine the allowable course substitutions and will advise the student which foundational courses to take. Students may satisfy requirements for Algebra 1 (MATH 5111) and Analysis 1: Functions of One Variable (MATH 5101) by taking qualifying exams in algebra 1 and in analysis 1 at the start of the program. Students may satisfy foundational course requirements if they demonstrate proficiency by passing an assessment exam in the course at the beginning of the semester or by demonstrating that they have taken a similar course and have adequate knowledge of the course material (syllabus and transcript are required; a brief oral examination is also required in that case). Academic advising will happen just before the start of each term and during the add/drop period in order to plan a student’s course registration for the term. A complete listing of foundational and advanced courses is available from the Department of Mathematics and the graduate dean’s office. Students are not permitted to register for more than two “readings” courses and three “topics” courses for credit toward the degree without explicit permission from the graduate dean. A minimum grade-point average (GPA) of 3.000 is required for degree conferral.
Teaching Requirement
Some teaching experience is required while in the program. Students must attend university-led TA training at the start of the program; attend a one-semester TA training course conducted by faculty from the Department of Mathematics teaching committee; spend one semester shadowing faculty in the undergraduate classroom; and perform recitations and grading for the undergraduate course they are shadowing.
Qualifying Exams
Qualifying exam sessions are given once in spring and once in fall. Students will be required to pass four qualifying exams: algebra 1, analysis 1, and two other exams. The possible additional topics for qualifying exams are algebra 2, analysis 2, combinatorics, geometry, ordinary differential equations, partial differential equations, probability, statistics, topology, and algebraic geometry. A qualifying exam may be taken twice by any student. Additional attempts may be allowed at the discretion of the graduate committee with permission from the graduate dean in the College of Science. Two qualifying exams should be passed no later than the end of the second year and all four by the end of the third year.
Doctoral Candidacy
PhD candidacy is reached when all of the following conditions are met:
- Completion of eight advanced courses
- Identification of an unsolved research problem
- Successful passing of four qualifying exams
- Assignment of PhD supervisor and creation of a 1-page initial plan
- Completion of a 3-page plan of research
- Completion of a 10-page progress report and a one-hour defense of proposal, presented to supervisor and three faculty members of graduate committee
Dissertation Requirement
Each candidate must complete a dissertation that embodies the results of extended research and makes an original contribution to the field. This work should give evidence of the candidate’s ability to carry out independent investigation and interpret, in a logical manner, the results of the research. There are two stages to this process:
- Stage 1: Students in the PhD program must have a dissertation supervisor within two years after joining the PhD program. The department views the failure of a student to find a supervisor within two years of joining the PhD program with concern and considers this sufficient cause to review the student’s status in the PhD program. The process of obtaining a dissertation supervisor always involves two choices—the student chooses the supervisor, and the supervisor chooses the student. For this reason, the department does not guarantee a dissertation supervisor for every student, but the department recognizes its responsibility to help the student find a satisfactory match. This aid is usually provided by the student’s graduate advisor, who should be familiar with the student’s progress in finding a dissertation supervisor. The dissertation supervisor guides the student’s further education as well as directs the student’s dissertation. The dissertation itself must represent an original solution of a problem in the chosen area of mathematics that makes a significant contribution to the mathematical knowledge in that area. Students must enroll in Dissertation or Dissertation Continuation while fulfilling the dissertation requirements.
- Stage 2 (dissertation defense): The final oral examination on the dissertation is held in accordance with university regulations and given by a dissertation committee of four faculty members (three from the university, including the supervisor, and one from outside Northeastern University). The dissertation supervisor should propose this dissertation committee to the graduate committee for its approval at least one month before the PhD dissertation defense.
Complete all courses and requirements listed below unless otherwise indicated.
Milestones
Four qualifying examinations
Annual review
Teaching requirement
Doctoral candidacy
Dissertation committee
Dissertation proposal
Progress report and presentation
Dissertation defense
| Code | Title | Hours |
|---|---|---|
| Complete 0–16 semester hours of the following courses: | 0-16 | |
| Analysis 1: Functions of One Variable | ||
| Analysis 2: Functions of Several Variables | ||
| Algebra 1 | ||
| Algebra 2 | ||
Advanced Coursework
| Code | Title | Hours |
|---|---|---|
| Complete 32 semester hours from the advanced coursework list. Only two readings and three topics courses are allowed. | 32 | |
Tracks
Complete one of the following three tracks:
Dissertation
| Code | Title | Hours |
|---|---|---|
| Dissertation Term 1 | ||
| Dissertation Term 2 |
Program Credit/GPA Requirements
32–56 total semester hours required
Minimum 3.000 GPA required
Pure Track
| Code | Title | Hours |
|---|---|---|
| Foundational Courses | ||
| Complete 0–8 semester hours from the following: | 0-8 | |
| Topology 1 | ||
| Geometry 1 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Probability 1 | ||
Discrete Track
| Code | Title | Hours |
|---|---|---|
| Foundational Courses | ||
| Complete 0–8 semester hours from the following: | 0 - 8 | |
| Analysis 2: Functions of Several Variables | ||
| Algebra 1 | ||
| Algebra 2 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Probability 1 | ||
| Mathematical Statistics | ||
Probability and Statistics Track
| Code | Title | Hours |
|---|---|---|
| Foundational Courses | ||
| Complete 0–8 semester hours from the following: | 0 - 8 | |
| Analysis 2: Functions of Several Variables | ||
| Algebra 2 | ||
| Quantum Computation and Information | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 1 | ||
| Probability 1 | ||
| Mathematical Statistics | ||
Advanced Coursework List
| Code | Title | Hours |
|---|---|---|
| Numerical Analysis 2 | ||
| Topology 2 | ||
| Riemannian Optimization | ||
| Graph Theory | ||
| Optimization and Complexity | ||
| Machine Learning and Statistical Learning Theory 1 | ||
| Functional Analysis | ||
MATH 7302 | ||
MATH 7303 | ||
| Commutative Algebra | ||
| Algebraic Number Theory | ||
MATH 7316 | ||
| Modern Representation Theory | ||
| Modern Algebraic Geometry | ||
| Topology 3 | ||
| Machine Learning and Statistical Learning Theory 2 | ||
| Probability 2 | ||
| Applied Statistics | ||
| Regression, ANOVA, and Design | ||
MATH 7346 to MATH 7361 | ||
| Morse Theory | ||
MATH 7374 | ||
MATH 7976 to MATH 8986 | ||
| Research | ||
| Topics | ||
| Only three topics courses are allowed. | ||
| Topics in Algebra | ||
| Topics in Algebraic Geometry | ||
| Topics in Representation Theory | ||
| Topics in Topology | ||
| Topics in Combinatorics | ||
| Topics in Probability | ||
| Readings | ||
| Only two readings courses are allowed. | ||
| Readings in Topology | ||
| Readings in Graph Theory | ||
| Readings in Algebra | ||
| Readings in Algebraic Geometry | ||
| Readings in Discrete Geometry | ||
| Readings in Probability and Statistics | ||
| Readings in Geometry | ||