Computational Science provides the interdisciplinary training for the scientists who derive and apply complex mathematical models for the simulation of structures and processes in nature, technology, economy and society.
The solution of large-scale numerical problems plays an increasingly important role for research and development in science and engineering, as well as business, economics, financial markets and medicine.
|Buoyancy fluctuations in early stages of a large-eddy|
|simulation of a breaking atmospheric gravity wave.|
Its basic tools, such as the Fast Fourier Transform technique or parallelization, have their foundations in applied mathematics and computer science. At an intermediate level these techniques are incorporated into either general or special purpose program packages, as, for instance, the mathematics toolbox MATLAB. In order to apply these tools within a particular scientific field, fundamental concepts of the given field have to be employed in order to set up models suitable for numerical simulation. Only an understanding of the scales, interactions and correlations involved allows the formulation of efficient, yet realistic models.
Integration of all levels into a two-year Master's program meets the increasing demand of science, the knowledge-based economy and society for interdisciplinary trained academics who do not simply apply "off the shelf" program packages as black boxes.
Computational Science at Goethe University is a two-year Master's program focusing on research.
Computational Science is a two-year program, building on a three-year Bachelor's degree. Of course, four-year Bachelor's graduates are also encouraged to continue their studies in Frankfurt. In this case all suitable credits will be recognized.
The primary goal of our M.Sc. program is training students for computer-based research and development. The program targets outstanding students with a Bachelor's degree in Computer Science, Geoscience, Mathematics, Meteorology, Neuroscience or Physics, but is also open to exceptional students with a degree in Engineering. Building on the common platform of mathematical and methodological expertise acquired during the Bachelor's studies, the Master's program leads students towards the current state-of-the-art of research, both with respect to computational techniques and with respect to the specific scientific field in which students apply these computational techniques:
|Online Event Display of ALICE experiment: reconstructed Pb-Pb collision|
On the one hand a step by step specialization leads the students of the natural sciences to the state-of-the-art in one particular area of current research. This area of specialization is left to the student's choice, a variety of options being offered. In this respect, Computational Science provides the same level of training as a Master's program in one of the natural sciences, restricted, however, to the theoretical branch. In addition, students learn the essentials of modelling and simulation as well as of high-performance computing. So the program is intended for students of the natural sciences who want to familiarize themselves with the modern and often indispensable tool of scientific computing, in order to use it in their original field of science.
On the other hand, the program allows all students, and in particular those with a Bachelor's degree in computer science or mathematics, to focus an method development. Rather than deepening their knowledge in one of the natural sciences, these students acquire in-depth expertise in the field of scientific computing, in high-performance computing or in math finance.
At the same time the comparatively broad education in applied mathematics and computer science together with the interdisciplinary curriculum ensure a high degree of flexibility in the employability of the graduates. The M.Sc. in Computational Science is well prepared for entering non-traditional careers. The program thus also targets students who are primarily out for a methodological training, in order to apply the methods in a non-scientific environment.
|Ultra-Relativistic QMD: Pb-Pb collision at 160 GeV/A|
Computational Science at Goethe University emphasizes interdisciplinary exchange and early participation of students in research and is open to international students.
The structure of the curriculum is particularly open and highly interdisciplinary.
|(Copyright Stadt Frankfurt am Main)|
In the curriculum, particular emphasis is placed on individual research. A student's thesis project will directly address an open question at the forefront of science. The actual work on the project is preceded by a preparatory phase in which students familiarize themselves with the scientific techniques: they study the appropriate literature, become acquainted with the relevant computational techniques and learn to formulate a research proposal. The graduates of this program are self-driven and perfectly trained for independent research.
Moreover, everyday contact with fellow students with different cultural backgrounds and integration in international research collaborations or networks during the Master's project strengthen the inter-cultural skills of our graduates.
Last, but not least, Frankfurt is an international city with a broad cultural scene: a first-rate opera house, some 30 theaters and almost 40 museums attract thousands of visitors each year to the metropolis on the Main river. The city also offers a wide variety of sports and leisure activities to fit any taste.
Computational Science opens a variety of career paths in- and outside science.
The graduates of the Master's program Computational Science have a variety of options for professional employment. Graduates of the M.Sc. in Computational Science have experienced a much broader training in computational methods than graduates of the traditional programs in the individual natural sciences. Combined with their in-depth knowledge in the specific scientific field, this broad education greatly enhances the flexibility of the graduates. Some examples for career paths are:
|CSC Opteron Cluster|
Chemical and pharmaceutical industry
More and more often the synthesis of new materials and, in particular, of new pharmaceutical substances (drug design) starts with extensive computer simulations, in order to identify the most suitable class of compounds.
The analysis of the human genome is a prominent example for computer-based research in the private sector. It is to be expected that the demand for specialists in this area will continue to increase in the years to come.
Aircraft and automobile design
The examination of the aerodynamics and the elastic properties is one of the most costly steps of the development of new cars or aircrafts. Today, in many cases simulation programs are used for this task.
Insurance business, Banking, Investment Banking
Both for insurance companies and for private and public banks the computer-based evaluation of math finance models plays an increasingly important role. In both cases the simulation of stochastic processes is of interest, for instance for estimating the probability for the occurrence of damage. The numerical methods which are utilized for these calculations are exactly the same as those applied in the context of research in the natural sciences.
Reinsurance business, public service
For reinsurance companies, but also in the political arena, the evaluation of realistic estimates for the probability for the occurence of catastrophies and the simulation of their consequences become more and more important. The same is true for the development of the local and global climate. In both cases Computational Science provides the means.
An ambitious and current task in the domain of computer simulations is the medium and long-term weather forecast, covering forecast times of 4 to 12 days. The graduates of the Master's program Computational Science have the option to acquire the knowledge required for professional work in the numerical weather forecast, covering both large-scale and mesoscopic-scale phenomena.
In basic research computer simulations and numerical modeling are not only relevant for the theoretical branches of brain research, (bio)chemistry, geoscience and (bio)physics, but also for the design of large-scale experiments.
So, there are many good reasons to join us!
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