Doctoral Programs

The School of Math offers or participates in six different multidisciplinary PhD programs, each with their own curriculum and set of requirements as described below.  In the first year or two of the program students focus on the coursework required to pass the comprehensive exams. By the third year of study, students should have selected a major field and a research advisor. All students must satisfy a "minor" requirement of nine additional credit hours of graduate or advanced undergraduate coursework outside the School  or away from their area of specialization, with a GPA of at least 3.0. The completion of the program, which culminates in writing a dissertation, takes about 5 years. All Doctoral students should also be aware of the general Institute wide Requirements for the Doctoral Degree described in the GT Catalog.

 

The PhD program in Math is designed to train academic mathematicians, in a wide range of subdisciplines, and mathematical research scientists working in government or the private sector. By far, most of the PhD students in the School are enrolled in this program. PhD students in Math may work with any faculty member in the School.

 

The PhD in ACO is a multidisciplinary program sponsored jointly by the College of Computing, the H. Milton Stewart School of Industrial and Systems Engineering, and the School of Math. Any affiliated faculty member can supervise the research of any ACO student regardless of departmental affiliation.The director of the ACO program is Prasad Tetali.

 

The PhD in CSE is a highly interdisciplinary program designed to provide students with practical skills and theoretical understandings needed to become leaders in the field of computational science and engineering. This is a joint program between the Colleges of Sciences, Computing, and Engineering. CSE applicants who choose Math as their home school are expected to have a strong background in Math. The School's lead advisor and coordinator of the CSE program is Sung Ha Kang.

 

The mission of the Bioinformatics PhD Program is to educate and prepare graduate students to reach the forefront of leadership in the field of bioinformatics and computational biology; and to integrate research and education on the use of information technologies in biology and medicine. The School's lead advisor and coordinator of the Bioinformatics program is Leonid Bunimovich.

 

The mission of QBios is to educate students and advance research in quantitative biosciences, enabling the discovery of scientific principles underlying the dynamics, structure, and function of living systems. The School's lead advisor and coordinator of the QBioS program is Hannah Choi.

 

Machine learning aims to produce machines that can learn from their experiences and make predictions based on those experiences and other data they have analyzed. This field crosses a wide variety of disciplines that use data to find patterns in the ways both living systems, such as the human body and artificial systems, such as robots, are constructed and perform. The School's lead advisor and coordinator of the Machine Learning program is Vladimir Koltchinskii

 

Prospective Students

Students with a bachelor's degree in Mathematics, or related fields, and good preparation for graduate study may apply for admission directly into the doctoral program. Completion of the master's degree is not a prerequisite. Other requirements include the GRE tests, and the TOEFL exam for international students.  Virtually all students admitted to our PhD programs are offered full financial support including tuition waivers and stipends in the forms of teaching or research assistantships.

 

Alumni

The list of all PhD alumni of the School of Math and their first employment after graduation, going back to 1965.