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Overview

Mathematical models and methods, especially from the field of optimization and simulation, are of immense importance for numerous key areas of science and business. Nowadays, for example in sectors such as the automotive, aircraft and aerospace industries, the electrical industry or the chemical industry, one is able to understand and master complete technical processes by means of numerical simulation in the computer before the actual production. Expensive or polluting test arrangements no longer have to be built and valuable raw materials can be saved. In resource, sales and financial planning, computer-aided simulation calculations also form the basis for early optimization approaches.

However, in order to be able to carry out complex simulations professionally, a well-founded theoretical training is required, which is supplemented by pronounced application references. This is what the new Master’s degree in Optimization and Simulation does.

The students are enabled to make independent scientific contributions in modeling, optimization and simulation. In addition to qualifying for many demanding jobs in companies, the master’s degree also fulfills the requirements for employment in the higher public service or a subsequent doctorate.

PROGRAMME STRUCTURE

Building on a basic mathematical and technical education, the course teaches, among other things:

  • a wide range of training in optimization and simulation strategies,
  • Understanding the language of mathematicians and engineers,
  • practice-oriented knowledge of the corresponding application and computer algebra programs,
  • Special knowledge in selected subject areas of mathematical modeling and optimization and simulation methods,
  • Management knowledge with special consideration of computer-aided approaches,
  • Ability and practical skills to independently solve tasks in future professional fields.

The master's thesis concludes the course and is usually carried out in cooperation with companies.

summer semester

  • Discrete optimization
  • Management skills
  • Seminar partly in English
  • Elective module from the simulation catalog
  • Elective module from the simulation catalog

Winter semester

  • Bionic methods of optimization
  • Project
  • Risk management
  • Elective module from the simulation catalog
  • Elective module from the simulation catalog

3rd semester

  • master thesis
  • colloquium

ENTRY REQUIREMENTS

Successfully completed engineering or mathematical studies with good scientific and mathematical knowledge (final grade Bachelor 2.9 or better) as well as satisfactory English language skills.

CAREER PROSPECTS

The demand for experts, specialists and executives in the field of computer-aided optimization and simulation is great, so that excellent career prospects arise for graduates of the master’s course. In its accreditation report, AQAS expressly states: "... the Master's degree in Optimization and Simulation, thanks to its special focus, enters a niche in the market."

The number of specific occupational fields in a wide variety of industries that are presented in an overview module is numerous. Only the following are mentioned as examples:

  • Technical calculations, for example strength calculations, vibration analyzes, image data analyzes, weather calculations, fault calculations, statistical analyzes of communication channels or encryption.
  • Technical simulations, for example traffic simulations, network simulations, aerodynamic simulations or reactor simulations.
  • Technical system analyzes, for example for the modeling of process engineering processes, for process data processing or for computer-aided product analyzes.
  • Modeling and optimization of production processes, for example to solve machine occupancy problems or to organize queues.
  • Sales and resource planning, for example storage optimization, optimization of ordering systems, material requirements determination and determination of optimal sales prices.
  • Finance and risk management, for example for reliability calculations, development of risk control systems based on company simulations and optimization of the company's individual financing structure.


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