Our Master of Science in Mathematics provides you with basic graduate training in mathematics. As a math graduate student, you will choose from a widely ranging program of study that may focus on pure or applied mathematics. The program's flexible coursework is designed to prepare you for employment in areas such as academia, government, business or industry or for further graduate study. You will work with your graduate advisor to design a program of study geared towards your interests and goals.
Upon graduation, you will have achieved a mastery of fundamental knowledge in a broad range of mathematical areas as well as a deeper understanding of at least one particular sub-field of mathematics and/or related field. You will hone your ability to solve problems and communicate solutions and concepts clearly and in rigorous mathematical language. Those of you who choose the "Thesis Option" will also be able to demonstrate an ability to present and defend research work in oral, written, and graphic forms.
Graduates of the MS Program have gone on to employment in areas such as academia, government, business or industry or have gone on to be accepted at competitive PhD programs.
See Tuition and Financial Aid information for GSAS Programs. Note: This program is eligible for federal loans and Tufts tuition scholarships.
Average Salary: $60K - $90K
Would Recommend the Program: 80%*
Average Age: 24
*Sources: GSAS-SOE Graduate Exit Survey 2020 - 2021 and Academic Analytics (Alumni Insights)
Research/Areas of Interest: Noncommutative harmonic analysis, representations of Lie groups, integral geometry, and Radon transforms
Research/Areas of Interest: Scientific computing and numerical analysis; Parallel multigrid and multilevel methods for large-scale coupled systems; Efficient numerical methods for reservoir simulation, fluid-structure interaction, and other applications.
Research/Areas of Interest: Scientific computing and numerical analysis: Efficient computational methods for complex fluids, plasma physics, electromagnetism and other physical applications.
Research/Areas of Interest: Applied dynamical systems, applied probability theory, kinetic theory, agent-based modeling, mathematical models of the economy, theoretical and computational fluid dynamics, complex systems science, quantum computation Current research emphasis is on mathematical models of economics in general, and agent-based models of wealth distributions in particular. The group's work has shed new light on the tendency of wealth to concentrate, and has discovered new results for upward mobility, wealth autocorrelation, and the flux of agents and wealth. The group's mathematical description of the phenomenon of oligarchy has also shed new light on functional analysis in general and distribution theory in particular. Secondary projects include new directions in lattice Boltzmann and lattice-gas models of fluid dynamics, kinetic theory, and quantum computation.
Research/Areas of Interest: Anomalous diffusion, mathematical neuroscience
Research/Areas of Interest: Geometric group theory, low-dimensional topology, CAT(0) spaces
Research/Areas of Interest: Geometrically motivated hyperbolic dynamics — Hasselblatt's research, undertaken with colleagues from several continents, is in the modern theory of dynamical systems, with an emphasis on hyperbolic phenomena and on geometrically motivated systems. He also writes expository and biographical articles, writes and edits books, and organizes conferences and schools. His publication profile can be viewed at https://mathscinet.ams.org/mathscinet/author?authorId=270790 (with a subscription). Former doctoral students of his can be found in academic positions at Northwestern University, George Mason University, the University of New Hampshire, and Queen's University as well as among the winners of the New Horizons in Mathematics Prize.
Research/Areas of Interest: Numerical Linear and Multilinear Algebra, Scientific Computing, Image Reconstruction and Restoration
Research/Areas of Interest: The structure and representations of algebraic groups
Research/Areas of Interest: Tomography is an inverse problem, and the goal of tomography is to map the interior structure of objects using indirect data such as from X-rays. Integral geometry is the mathematics of averaging over curves and surfaces, and it is the pure math behind many problems in tomography. Integral geometry combines geometric intuition, harmonic analysis, and microlocal analysis (the analysis of singularities and what Fourier integral operators do to them). I have proven support theorems and properties of transforms integrating over hyperplanes, circles and spheres in Euclidean space and manifolds. Because of the mentorship of Tufts physics professor and tomography pioneer, Allan Cormack (Tufts' only Nobel Laureate) I developed X-ray tomography algorithms for the nondestructive evaluation of large objects such as rocket bodies, and this motivated my research in limited data tomography In limited data tomography problems, some tomographic data are missing. I developed a paradigm to describe which features of the object will be visible from limited tomographic data and which will be invisible (or difficult to reconstruct). I proved the paradigm using microlocal analysis. Often artifacts are added to tomographic reconstructions from limited data, and colleagues and I recently used microlocal analysis to prove the cause of these added artifacts and to predict where they will occur. Collaborators and I have developed local algorithms for electron microscopy, emission tomography, Radar, Sonar, and ultrasound. In each case we use microlocal analysis to determine the strengths and weaknesses of the problem and to refine and improve the algorithms.
Research/Areas of Interest: Geometric Group Theory/Topology
Research/Areas of Interest: To each point on a curve, one can often associate in a natural way a line or plane (or higher dimensional linear variety) that moves with the point in the curve. This set of linear spaces is called a vector bundle. Vector bundles appear in a variety of questions in Physics (like the computation of Gromov-Witten invariants) . Moreover, they provide new insights into old mathematical problems and have been used to give beautiful proofs to long standing conjectures as well as striking counterexamples to some others.
Research/Areas of Interest: Algebraic geometry, topology, and differential geometry
Research/Areas of Interest: Hyperbolic manifolds and orbifolds, low-dimensional topology, group actions