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Faculty of Mathematics, Physics & Computer Science

Scientific Computing, Master of Science (M.Sc.) – October 2019

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Module Overview

The master's programme consists of the following six module areas:

A. Numerical Mathematics

Module A1: "Numerical Methods for Differential Equations” 8 ECTS

Elective Module A2: “Advanced Topics in Numerical Mathematics” 8 ECTS

Currently, possible choices are

  • Module A2.1 „Numerical Methods for Special Types of Differential Equations“
  • Module A2.2 „Constructive Approximation Methods“
  • Module A2.3 „Mathematical Control Theory“
  • Module A2.4 „Nonlinear Optimization“
  • Module A2.5 „Optimization with Differential Equations“

A1, A2 together with B1 is the foundation of the master’s programme.


B. Modeling and Simulation

Module B1: “Applied functional analysis” 8 ECTS

Elective Module B2: “Modeling and Simulation” 12 ECTS

Currently, modules can be chosen from

  • Module B2.1 „Partial Differential Equations and Integral Equations“
  • Module B2.2 „Modeling with Differential Equations“
  • Module B2.3 „Support Vector Machines“
  • Module B2.4 „Statistical Machine Learning“
  • Module B2.5 „Simulation of Many-Particle Quantum Dynamics“ 
  • Module B2.6 „Molecular Dynamics“
  • Module B2.7 „Simulation of Biofluids“
  • Module B2.8 „Biomolecular Modeling“
  • Module B2.9 „Foundations of Biological Computer Science“
  • Module B2.10 „Advanced Science of Strength of Materials“

At least 8 ECTS must not stem from the mathematical curriculum. 

Module B3: “Industrial Internship” 8 ECTS

Either a 6 weeks industrial internship or another module from D1 / B2.

Module B4: “Modeling Seminar” 10 ECTS

Each year, a one week modeling seminar will be held in which students apply their abilities to complex real world problems.


C. High-Performance Computing

Elective Module C1: “High-Performance Computing” 12 ECTS

Currently, modules can be chosen from

  • Module C1.1 „Algorithms and Data Structures II“
  • Module C1.2 „Algorithms and Data Structures III“
  • Module C1.3 „Parallel and Distributed Systems I“
  • Module C1.4 „Parallel and Distributed Systems II“
  • Module C1.5 „High-Performance Computing“
  • Module C1.6 „Parallel Algorithms“

Module C2: Practical course “Parallel Numerical Methods” 2 ECTS


D. Scientific Computing

This is the pivotal area of the master’s programme.

Elective Module D1: “Scientific Computing” 16 ECTS

Currently, modules can be chosen from
​ 

  • Module D1.1 „Fast Methods for Differential and Integral Equations“
  • Module D1.2 „Efficient Numerical Treatment of Multiscale Problems“
  • Module D1.3 „Numerical Methods for Uncertainty Quantification“
  • Module D1.4 „High-dimensional Approximation“
  • Module D1.5 „Data Analytics I“
  • Module D1.6 „Data Analytics II“

Elective Module D2: “Special Skills in Scientific Computing” 4 ECTS

A specialisation module in the area of Scientific Computing or Numerical Mathematics.


E. Soft Skills 2 ECTS

Participation in seminars of in total 60 hours which improve key qualifications such as presentation techniques, scientific writing,  teamwork, literature research and personality development.


F. Master’s Thesis 30 ECTS

We encourage students to prepare their master’s thesis in corporation with industry or international experts. Students receive compensation for travel expenses during research stays.

We recommend the following curriculum (PDF).

Curriculum M.Sc. Scientific Computing

Webmaster: Massimo Pinzer-Braese

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