Master Scientific Computing

Scientific Computing is the challenging combination of applied mathematics and computer science to solve application problems by means of numerical methods.

The program, run by the Faculty for Mathematics and Computer Science in close collaboration with the Interdisciplinary Center for Scientific Computing (IWR) teaches students both the theoretical concepts of computer-based mathematical modelling and the practical aspects of realising complex algorithms in scientific software. By studying an application area as a minor subject, the education is focussed on real-world problems and the interdisciplinary communication that shapes the modern world of research & development.

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Examinations and Credits Mathematics

The Office for Examinations and Credits Mathematics administers examination results in the bachelor's and master's programs in mathematics, including “Mathematics of Machine Learning and Data Science”, and the master's program in “Scientific Computing”. The Office also issues transcripts and certificates of academic achievements.

heiCO

Campus-management system for all processes of the “student life cycle“ in a single web-based system: from application and admission, creating your study schedule, examination administration, to graduation

Download Center

For your convenience, we have collected all forms and documents available for download on the various static pages of the faculty website.

Facts and Figures

Table

Degree
Master of Science (M. Sc.)
Type of Study
Consecutive
Beginning of Program
Winter and summer semester
Standard Period of Study
4 semesters
Languages
English, some German
Application Procedure
Consecutive master's program with access restriction

Study Plan

The first year consists of courses in the three areas of this master program: Mathematics, Computer Science and a Field of Application. In the second year students prepare and conduct their research project. This phase is started with two specialization lectures and leads to a master project. To this end, students should choose a combination of courses in terms 1, 2 and 3 leading to a specialization within the master course.

Program Overview

Mathematical methods taught in this master program include:

  • Numerical methods for ODE and PDE
  • Statistics and data analysis
  • Differential geometry and computer algebra
  • Linear and non-linear optimization methods
  • Computational methods in fluid dynamics

Computer Science methods list for example:

  • Parallel computing
  • Scientific visualization
  • Mixed-integer programming
  • Spatial databases
  • Image processing techniques

Applications for Scientific Computing come from:

  • Physics and Astronomy
  • Robotics
  • Weather and Climate Modelling
  • Text and Data Mining
  • Theoretical Chemistry
  • Biology
  • Scientific Visualization
  • Economics
  • Social Sciences
  • Cultural Heritage

The program is linked with HGS MathComp, the doctoral school for mathematical and computational modeling at Heidelberg University. Top students in the first year course will get an invitation to join the doctoral school already for the second master year, opening the possibility to a direct integration into the HGS MathComp PhD program, a master course directly leading to a PhD project (research oriented master track).

Older admission regulations, degree regulations, and course handbooks can be found in the download center.