Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
, differential equations, coding theory, image analysis, and mathematics education. The department places a strong emphasis on student mentoring, interdisciplinary collaboration, and preparing graduates
-
methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and structure-aware learning; and the
-
Professor, Associate Professor, or Full Professor (with the possibility of appointment at Distinguished Professor for exceptional candidates). The department has identified priority areas of differential
-
unsupervised learning. These methods will be based on new classes of partial differential equations on graphs and new graph neural network models based on diffusion processes. The developed algorithms will be
-
Distribution of Effort will be 25% teaching, 70% research, and 5% departmental service. The successful candidate is expected to pursue a vigorous research program in the theory of Partial Differential Equations
-
for Science and Engineering I,II,III; Applied Calculus intended for non-math intensive majors (e.g., Biology, Economics, Psychology); Differential Equations; Linear Algebra; Statistics to include data and
-
Parametric integrators approximate solutions of (high-dimensional) partial differential equations by restricting the numerical approximation to a closed form that nonlinearly depends on, and is
-
-month, full-time (1.0 FTE), position. The search is open to all areas of mathematics, with candidates in partial differential equations (PDE) and algebra especially encouraged to apply. Candidates should
-
written in terms of differential equations. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group
-
This PhD project will investigate partial differential equations arising from kinetic models, with a particular focus on variational methods. The research will explore how variational structures