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Scientific Computing

Lupe
Master Program Scientific Computing
Degree
Master of Science
Duration
4 semesters
Credit points
120 ECTS
Starts in
Winter semester and summer semester
Admission
non-restricted
Languages
German/English

Development of new technology is a key answer to economic and social demands for improved sustainable quality of life. Advanced Scientific Computing is an enabling technology for scientific discovery and engineering design. The remarkable development of large scale computing has turned Scientific Computing into the scientific “third pillar”, complementing theory and experiment.
Scientific Computing has transitioned from providing insight to also providing reliable numbers for design in engineering disciplines, thereby shortening and economizing the design cycle for products and processes. Scientific Computing is a key technology for applications in medicine, climate, energy and environment, advanced materials, biology, nano-manufacturing, and many, many others. Virtual prototyping is ubiquitous in most sectors of industry. The businesses in Telecom, IT, Power generation and distribution, Aerospace, Financial industries, and Automotive are broad-spectrum users, relying on in-house resources, academia, research institutes, and software developers as providers.

Although Scientific Computing research is often initiated by challenges of certain application areas, the subject of Scientific Computing is the tools developed which are universal and generally transferable to other applications. The computer science and mathematics skills needed are quite broad, because the strength of such generic tools lies in their innovative power to bring techniques from one discipline to bear on problems from very different settings. It follows that advances in modeling need both deeper insight in mathematics, familiarity with the application area, and with high-performance computer software issues.

The Master program Scientific Computing at TU Berlin is strongly based on applied mathematics and in particular on numerical analysis. It consists of seven areas.

Area 1: Scientific Computing, 27 ECTS credit points
Here the student can choose among different courses, mostly in Numerical mathematics. The course Wissenschaftliches Rechnen (Scientific Computing) is mandatory.

Area 2: Applied Mathematics, 20 ECTS credit points
Here different courses in applied mathematics can be chosen

Area 3: Applied discipline, 19 ECTS credit points
The student can choose courses from one of the applied disciplines physics, chemistry, engineering sciences, biology or medicine. The non-mathematical subjects take an important part of the program with an amount of approx. one semester.

Area 4: Free choice, 5 ECTS credit points
Here one or more courses offered from the TU Berlin can be chosen.

Area 5: mathematical Seminars, 12 ECTS credit points
Here two seminars must be taken.

Area 6: Internship, 7 ECTS credit points
A full-time industrial internship of at least six weeks is compulsory and usually is completed during the break/holidays before or after the third semester. Passing the internship the student becomes acquainted with problems from research and development. As far as supervision is ensured the internship can be done at an institution outside the University.

Area 7: Master thesis, 30 ECTS credit points

The Master Thesis should be designed considering the current state of research. This is guaranteed by intensive research work of the teaching staff.
The topic of the master thesis can be chosen in the field of applied mathematics as well as in the applied discipline. The Master thesis can also be written in collaboration with an industrial partner.

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Master's programs at TU Berlin