Program Overview

Program Overview

The Master's program in Industrial Mathematics and Data Analysis is a four-semester program that provides students with a solid foundation in mathematical methods for data analysis and industrial applications. The program is designed to prepare students for a career in industrial research and development, data analysis, or other operational areas.

Program Structure

The program consists of 120 credit points and can be divided into the following areas:

• Foundations (18 CP): lectures on "Numerical Methods for PDE" and on "Mathematical Methods for Data Analysis and Image Processing" (9 CP each)
• Area of Specialization (27 CP): 2 lectures (electives 9 CP each), plus one more lecture or two seminars ("Compulsory elective module", 9 CP)
• Extension (18 CP): 1 lecture (9 CP) and 2 seminars (9 CP together), independent from area of specialization
• Modeling Project (15 CP)
• Technical Application Subject (12 CP)
• Master's Thesis (30 CP)

Admission Requirements

The admission requirements for the program include:

• A Bachelor's degree in a relevant field (e.g., mathematics, computer science, engineering)
• Sound knowledge in real analysis, multivariate calculus, and linear algebra (matrix theory)
• Ordinary differential equations: Peano's theorem, Picard-Lindelöf's theorem
• Lebesgue integration: L_p spaces, Lebesgue's dominated convergence theorem
• Functional analysis: Banach and Hilbert spaces, linear operators, weak convergence
• Probability theory: random variables, probability distributions, law of large numbers
• Numerical mathematics: linear systems, nonlinear equations and systems, interpolation and extrapolation, numerical integration, ordinary differential equations

Career Prospects

Graduates in industrial mathematics work in various fields, especially in the R&D departments of industry, in software development or as consultants for IT and data processing. The education in Industrial Mathematics and Data Analysis meets the professional requirements and the demands of companies very well, making the career prospects for industrial mathematicians excellent.

Research Areas

The program is closely tied to the Center for Industrial Mathematics (ZeTeM), whose declared goal and central task is to impart the modern mathematical methods of industry and science. The research areas include:

• Mathematical methods for data analysis and image processing
• Numerical methods for PDE
• Machine learning
• Inverse problems
• Applied statistics
• Parameter identification
• Optimal control
• Discrete optimization
• Adaptive FEM

Faculty and Research

The program has 14 full-time professorships (including cooperative and junior professorships and interim professorships) for the mathematical subjects in Department 03. The faculty members cover the teaching for degree programs in mathematics, math education, industrial mathematics, and elementary mathematics. Additional teaching is provided by honorary professors, lecturers from non-mathematical fields, and temporary lecturers.

Contact and Advice

For more information about the program, please contact the Study Center Mathematics or the Student Representative Council (StugA) Mathematics. The program's homepage provides detailed information about the program structure, admission requirements, and research areas.