MSc Computer Simulations for Science and Engineering COSSE

The master's programme in Computer Simulations for Science and Engineering (COSSE) is a two-year programme including compulsory mobility for the students. The programme includes three semesters of courses followed by the fourth research semester spent on the master's degree project (30 ECTS) under the supervision of both degree-awarding universities. The joint supervision of the degree project work includes the possibility that the topic is chosen according to specialisations offered by the degree-awarding universities individually.

The students enter one of the universities and continue the second year at one of the other universities in another country). As a general rule, students will be admitted to TU Berlin for the first year for coursework amounting to at least 60 ECTS credits. Upon request, students may enter KTH or TU Delft for their first year of studies (coursework amounting to at least 60 ECTS) if approved by PAG and endorsed by the said university. Admission for the second year can, in this case, be either TU Berlin or KTH/TU Delft as approved by PAG and endorsed by the university responsible for admitting the student to the second year.

The second-year university offers coursework (at least 30 ECTS credits) and supervision of the master's degree project (30 ECTS credits). This includes a choice of specialisation at the chosen university:

• KTH: Biocomputing, bioinformatics, machine learning, computational fluid dynamics, numerical linear algebra, computational physics, numerical analysis;
• TU Delft: computational fluid dynamics, numerical linear algebra, high-performance computing, data assimilation
• TU Berlin: Optimal Control, Control Theory, Numerical Linear Algebra, Numerical Analysis

The specialisations offered reflect some of the research areas of each institution and their spearhead competencies. A student can choose a specialisation different from the proposals above if the PAG agrees. The programme consists of core courses, preparatory courses, and elective courses. Additionally, extracurricular courses can be taken.

Year 1

• 20085 Scientific Computing
• 20835 Numerical Linear Algebra
• 20166 Numerical Mathematics II for Eng.
• 20098 Project Numerical Analysis
• 20089 Numerical Mathematics II
• 20063 Differential Algebraic Equations
• 20156 Control Theory
• 20080 Model Reduction
• 20372 Mathematical Visualization I
• 20382 Nonlinear Optimization
• 20427 Variational Methods and Optimal Control
• 20826 Advanced Topics of Numerical Linear Algebra
• 20825 Advanced Topics of Numerical Linear Algebra
• 20152 Mathematical Seminar
• 40550 Machine Learning I
• 40551 Machine Learning II
• 40548 Machine Intelligence I
• 40549 Machine Intelligence II

Year 2

The second-year universities offer many possibilities for specialisation in different topics of CSE. The mandatory master's degree project (30 ECTS credits) can be carried out at host departments, other departments at host universities, or companies. The following list provides an overview of elective courses. You can choose according to your interest, prerequisites, and the subject of the degree project. The list is not exhaustive. Moreover, not all courses may be given every year. They include:

• AK2030 Theory and Methodology of Science 4.5 C
• SA2001 Sustainable development and research methodology in mathematics 3 C
• SF2566 Advanced Individual Course in Sc Comp 6 P1+P2
• SF2567 Project course in Scientific Computing 7.5 P1+P2
• SF2565 Program construction in C++ for Sc Comp 7.5 P1+P2
• DD2421 Machine Learning 7.5 P1
• DD2434 Machine Learning (Adv Course) 7.5 P2
• SF2935 Modern Methods of Statistical Learning 7.5 P2
• DD2435 Mathematical Modeling of Biological Systems 9 P1+P2
• SK2532 Biomedicine for engineers 7.5 P1
• BB2441 Bioinformatics and Biostatistics 7.5 P1
• BB2280 Molecular Modeling 7.5 P2
• SF2832 Mathematical Systems Theory 7.5 P2
• SF2863 Systems Engineering 7.5 P2
• SF2866 Applied Systems Engineering 7.5 P1
• SF2942 Portfolio Theory and Risk Management 7.5 P1
• SF2980 Risk Management 7.5 P1
• SF2956 Topological data analysis

Students in the master's programme in Computer Simulations for Science and Engineering will become very familiar with the tools of CSE, which include:

• mathematical modelling techniques,
• simulation techniques (discretisations, algorithms, data structures, software in CSE),
• and analysis techniques (data mining, data management, visualisation).

The students will become experts in the generic tools as applied to one of the specialisations offered by the universities. Upon graduation, the students will have acquired:

• familiarity with selected scientific and engineering application areas and their mathematical models.
• a knowledge base and skills ranging from formulating mathematical models to constructing software for high-performance computer architectures.
• effective communication skills for interacting on written and oral presentations with the professional community as well as management and society at large.
• a degree of independent and critical appraisal of the capability and limitations of, and results produced by, computational modelling.

As to career opportunities, a degree from the master's programme in Computer Simulations for Science and Engineering opens several opportunities:

• to join the international research community by continuing PhD studies in the CSE and science/engineering fields where simulation and high-performance computing are applied: fluid dynamics, electromagnetics, molecular physics, quantum chemistry, material science, chemical engineering, structural mechanics, biocomputing, and many more.
• to gain employment in "end-user" high-tech industry and "provider companies", using and developing tools for advanced computer simulation in, for example, the pharmaceutical, automotive, materials, aeronautics, power generation, and microelectronics industry.
• to start new innovative companies which are based on CSE expertise.

The programme is highly research-oriented. So far, roughly two-thirds of the graduates have continued with a PhD position at the consortium partners KTH, TU Berlin, and TU Delft, as well as other leading international universities, for example, MIT (USA), Oxford University (UK), Purdue University (USA), Uppsala University (Sweden), ETH (Switzerland), Karolinska Institute (Sweden), University Melbourne (Australia), INRIA (France), Simon Fraser University (Canada), UPC Barcelona (Spain), NTU Singapore, and many others.

The graduates of this programme are also in high demand in the labour market. Graduates work in large and smaller companies such as Ericsson (Sweden), IBM Peking (China), BASF (Germany), Tata Steel (The Netherlands), DeCode genetics (Iceland), Sabic (India), AT Kearney (The Netherlands), HERE (Germany), TNO (The Netherlands) and many others.