With the rapid growth in the field of biology worldwide, there is a parallel emphasis on quantification in biology. This provides numerous opportunities for individuals trained in a quantitative discipline, such as mathematics, with additional training in topics that are essential to tackling biological problems.
The biomathematics major aims to provide students with this broad training. The affiliated faculty have a broad range of expertise, including biological modeling and data science. These topics are covered in the flexible course work, which allows for an emphasis in modeling or in data science. The Ph.D. degree offers students the opportunity to conduct research with faculty on a broad range of biological topics, and in some cases includes interaction with experimental labs at FSU or elsewhere. The program has been very successful at placing graduates in good postdoctoral and faculty positions both in and outside of the U.S.
This is a two-year program with 36 semester hours of courses and with seminars. Students develop skills in a number of areas for working on applications of mathematics to biology.
Students do research work in a variety of fields represented by the biomathematics faculty. Ph.D. students should complete all requirements for a master's degree and then pass the preliminary examinations.
Courses
- The student must have finished all course requirements.
- The student must also enroll in a seminar each fall and spring semester, and after the first year, at least one of these should be a specialized biomathematics seminar.
- In addition, the student must enroll in the math colloquium for at least two semesters.
Qualifiers
The student must pass 4 qualifying exams. The usual choices are from
- PDE I and/or II;
- Methods of Applied Math I and/or II; and
- Foundations of Computational Math I and/or II.
Qualifiers from pure mathematics are also applicable and can be taken.
Exemption from the written qualifier on an approved semester course is given for an A in the corresponding course.
Doctoral Candidacy Exam
The Candidacy Exam has two components:
The first is a written document focusing on some research topic in biomathematics, determined in consultation with the student's intended major professor. The second component is an oral public presentation of this document, followed by an oral exam by the student's doctoral committee. The exam is passed if the committee determines that both components have been satisfactorily completed.
The student must pass the doctoral candidacy exam by the end of the fall of year 3.
The core curriculum includes four courses to be satisfied by all students, and a weekly seminar. Remaining courses are chosen from a list of options, depending on the student's interest and faculty advice. Ph.D. and master's students in biomathematics complete 36 hours of approved coursework (not including seminars), of which a maximum of 6 credits can be taken S/U (pass/fail). At least five 3-hour courses must be in the Department of Mathematics. Students completing this coursework are awarded a master's degree.
Required courses
(Any one of these may be replaced by an appropriate biomathematics topics course with the permission of the director.)
Students must take the following core courses:
- MAP 5486 Computational Methods in Biology (Fall)
- MAP 5932 Spatial and Temporal Models in Biology (Spring)
- MAD 5306 Graph Theory and Networks (Fall) or other approved biomathematics course
- MAP 6437 Biomathematics Projects (Spring)
- MAP 6939 A Biomathematics seminar (1 hour credit each semester)
Interdisciplinary component:
Two courses from biology, chemistry, statistics, computer science or scientific computing. Typical choices are listed below. Other choices can be approved by the director of the program. Courses in biology and chemistry can, and probably should, be taken as S/U (pass/fail).
- PCB 5525 Molecular Biology (Biology department)
- BCH 5405 Molecular Biology (Chemistry department)
- PCB 5137 Advanced Cell Biology (Fall)
- BSC 5936 Membrane Biophysics
- PCB 5845 Cell and Molecular Neuroscience (Fall)
- STA 5176 Statistical modeling with application to biology (Fall)
- STA 5326 Distribution Theory (Fall)
- STA 5325 Mathematical Statistics (Spring)
- STA 5327 Statistical Inference (Spring)
- STA 5172 Statistics in Epidemiology
- STA 5179 Applied Survival Analysis (Spring)
- STA 5166 Statistics in Applications 1 (Fall)
- STA 5198 Epidemiology for Statisticians (Fall)
Additional mathematics courses:
From the following, for a total of 36 hours of listed courses (not including seminars) of which at least 5 courses are in the Department of Mathematics.
- MAP 5345, 5346 Elementary Partial Differential Equations I, II (Fall, Spring)
- MAP 5165, 5423 Methods in Applied Mathematics I, II (Fall, Spring)
- MAP 5932 Topological Data Analysis (Spring)
- MTG 5326, 5327 Topology I, II (Fall, Spring)
- MAS 5307, 5308 Groups Rings Vector Spaces I, II (Fall, Spring)
- MAA 5406, 5407 Complex Variables I, II (Fall, Spring)
- MAA 5616, 5617 Measure and Integration I, II (Fall, Spring)
- MAD 5403, 5404 Foundations of Computational Mathematics I, II (Fall, Spring)
- MAD 5738, 5739 Numerical Solution of Partial Differential Equations I, II (Fall, Spring)
(other graduate mathematics courses can be taken with approval of the director)
Visit the course descriptions page to learn more about some of these courses.
Expected background
- Calculus and multivariate calculus
- Ordinary differential equations
- Linear algebra
- Computer programming
Preferred background
A basic knowledge of the following areas will be helpful:
- Partial differential equations
- Statistics
- Mathematical Modeling
- Genetics
Any additional math courses will also be helpful.