Project Details
Projekt
GRK 1023: Identification in Mathematical Models: Synergy of Stochastic and Numerical Methods
Subject Area
Mathematics
Term
from 2004 to 2013
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 373214
The dissertation projects of the Research Training Group can all be subsumed under the theme "Identification in Mathematical Models". This includes classical inverse problems for partial differential equations (for example, inverse scattering theory and impedance tomography), classical parameter and model identification in statistics (for example by statistical learning algorithms) and, combining the two preceeding areas, new identification and classification problems in mathematics and in applications (for example classification of stochastic processes, geometric identification of fingerprints, identification of alien genes). The topics cover a broad range connecting theoretical mathematical problems, application relevant problems from numerical analysis and statistics, and interdisciplinary projects in collaboration with members of other sciences.
The concept of the integrated teaching and research programme aims at a solid education in applied mathematics both for science and industry. A main goal is to produce dissertations in current mathematical research at the borderline of numerical analysis and stochastics and to further the interaction of both areas with the aid of the projects. The interdisciplinary teaching programme with integrated elements from stochastics and numerical analysis will provide the graduate students with a solid foundation for a successful career both in science and in industry or business. Through the participation of scientists from physics, biology and medicine and the resulting interaction of mathematics and applications the students will be enabled to perform the mathematical modelling that is required with increasing importance in science, industry and society.
The concept of the integrated teaching and research programme aims at a solid education in applied mathematics both for science and industry. A main goal is to produce dissertations in current mathematical research at the borderline of numerical analysis and stochastics and to further the interaction of both areas with the aid of the projects. The interdisciplinary teaching programme with integrated elements from stochastics and numerical analysis will provide the graduate students with a solid foundation for a successful career both in science and in industry or business. Through the participation of scientists from physics, biology and medicine and the resulting interaction of mathematics and applications the students will be enabled to perform the mathematical modelling that is required with increasing importance in science, industry and society.
DFG Programme
Research Training Groups
Applicant Institution
Georg-August-Universität Göttingen
Spokesperson
Professor Dr. Thorsten Hohage
