MSc Computer Simulations for Science and Engineering
The master's programme in Computer Simulations for Science and Engineering (COSSE) focuses on the multidisciplinary field of Computational Science and Engineering, an enabling technology for scientific discovery and engineering design. It involves applied mathematics, mathematical modelling, numerical analysis, computer science, high-performance computing and visualisation. The programme is highly research-oriented, and two-thirds of graduates go on to PhD studies at leading universities worldwide.
Computer Simulations for Science and Engineering at KTH, TU Berlin and TU Delft
The master's programme in Computer Simulations for Science and Engineering (COSSE) is a programme within the multidisciplinary field of Computational Science and Engineering (CSE), which is an enabling technology for scientific discovery and engineering design. CSE involves mathematical modelling, numerical analysis, computer science, high-performance computing and visualisation. The remarkable development of large-scale computing in recent decades has turned CSE into the "third pillar" of science, complementing theory and experiment.
The programme is a two-year programme including compulsory mobility for the students. It is given jointly by KTH, the Technical University of Berlin in Germany and Delft University of Technology in the Netherlands. Students will enter one of the universities and continue in their second year at one of the other universities. Generally, students are admitted to TU Berlin for the first year.
The programme includes three semesters of courses followed by a fourth research semester spent on a master's degree project under the supervision of both universities attended. The students receive two degrees from both the first and second-year universities.
Learning outcomes
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.
Workshop
After the beginning of the second semester, students, scholars and teachers of all partner universities will meet for a joint workshop to advise students on their elective courses, including possible topics for their master's degree project. The workshop will include joint research and cultural activities and provide contacts to research departments in academia and industry.
Degree project
The master's degree project comprises 30 ECTS credits and is carried out in the second half of the second year of the programme. The project work may be performed in a research group at the institute or as a project in industry or consultancy company. The programme maintains a contact network spanning a large number of of companies, in order to provide a relevant degree projects for the students. Examples of company collaborations include for example COMSOL, Shell, Klarna, LKAB, Ericsson, Deepwater Energy BV, Sellpy, Electronic Arts, Tetrahedron B.
Previous degree projects
This is a two-year programme (120 ECTS credits) given in English. Graduates are awarded the degree of Master of Science from KTH and an equivalent degree from the attended universities, respectively. At KTH, the programme is given mainly on its Campus in Stockholm by the School of Engineering Sciences (at KTH).
Courses in the programme
The courses in the programme cover topics such as computational fluid dynamics, numerical linear algebra, high-performance computing, data assimilation, optimal control, control theory, numerical analysis, biocomputing, bioinformatics, machine learning.
Courses in the programme Computer Simulations for Science and Engineering
Students
Find out what students from the programme think about their time at KTH.
Future and career
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 is 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.
Sustainable development
Graduates from KTH have the knowledge and tools for moving society in a more sustainable direction, as sustainable development is an integral part of all programmes. The particular strength of mathematics is its high grade of abstraction, with the same mathematical model used to describe very different features in various areas of application. This versatility leads to the effect that once you can quantify phenomena, you will be able to investigate them independently of their source, for example, in science, engineering, society and the economy. Many of the UN goals of sustainable development are accordingly linked to Applied Mathematics, to name just a few: Good health and well-being, Affordable and clean energy, Decent work and economic growth, Industry, innovation and infrastructure, Sustainable cities and communities, Climate action, Life below water, Reduced inequality and others. The master’s programme in Computer Simulations for Science and Engineering provides the student with the knowledge and tools applicable for successful treatment. You will see examples of how to do this in different courses. It is not uncommon for the final master's degree project to be devoted to questions related to sustainable development and its various goals. The examples of sustainable development goals addressed by the programme are:
Examples of master’s degree projects relating to Affordable and Clean Energy are:
- Solar power forecasting with machine learning techniques (in collaboration with Vattenfall).
- Risk assessment for hydropower plants (in collaboration with Vattenfall Hydro).
- Control of smart grids for energy distribution (in collaboration with Ngenic).
- Optimisation in seasonal planning of hydropower plants (in collaboration with Power).
Examples of master's degree projects relating to Decent Work and Economic Growth are:
- The effect of Swedish laws on the inclusion of disabled persons.
- Financial sustainability of the Swedish income-based pension system (in collaboration with Pensionsmyndigheten).
- The effect of sustainability-oriented investments on the risk&return (in collaboration with COIN Investment Consulting Group).
Examples of master's degree projects relating to Industry, Innovation and Infrastructure are:
- Optimal traffic planning for autonomous vehicles (in collaboration with Volvo Construction Equipment).
- Optimal energy management for parallel hybrid electric vehicles (in collaboration with Scania).
- Optimal driving decision based on energy and time costs (in collaboration with Volvo).
Faculty and research
KTH
The programme is run by the Department of Mathematics. The Department of Mathematics at KTH hosts some of the strongest Swedish research groups in mathematics. It comprises four units: Mathematics, Mathematical Statistics, Optimisation and Systems Theory, and Numerical Analysis. Jointly, these units carry out research in a broad spectrum of mathematical disciplines, ranging from pure to applied mathematics. Some of the current larger research centres hosted at the department are:
- Random matrices, sponsored by the Wallenberg foundation
- Image processing, sponsored by SSF
- PDE, sponsored by the ERC/VR/Gustafsson's foundation
- MathDataLab, sponsored by Brummer & Partners
The research at the Division of Numerical Analysis includes numerical methods for stochastic and deterministic differential equations, computational modelling in systems biology, numerical methods for micro and complex flow, multiscale methods, finite element methods for multiphase flow. The researchers are working actively in many interdisciplinary cooporative partnerships, for example the Swedish e-Science Research Centre (SeRC), the Linné FLOW Centre, and with Karolinska Institutet. You will also have access to Sweden’s fastest supercomputers through the PDC Centre for High-Performance Computing. The faculty members Professor Anders Szepessy and Professor Anna-Karin Tornberg are members of the Royal Swedish Academy of Sciences.
TU Berlin
The programme is run at the Institute of Mathematics of Faculty II – Mathematics and Natural Sciences is an application-oriented research and teaching institute of Technische Universität Berlin. Our Institute offers courses in mathematics, mathematical economics, technomathematics (both as a bachelor's and master's) and scientific computing as well as extensive mathematics services for students attending other courses.
The Institute of Mathematics at Technische Universität Berlin distinguishes itself through its diverse cooperative partnerships within Berlin, nationwide and internationally. Hosting and participating in mathematical research training groups DFG, Deutsche Forschungsgemeinschaft, in DFG collaborative research centres and in DFG research units, acquisition of ERC grants as well as various prices and awards which emphasise the high level and international reputation of the institute.
The programme is run in close collaboration with the Berlin Mathematical School (BMS), a joint graduate school of the mathematics institutes of the three major Berlin universities. BMS is based at the Institute of Mathematics at TU Berlin, being funded within the framework of the German "Initiative for Excellence".
The Institute is strongly involved in the Research Center Matheon "Mathematics for Key Technologies", an internationally renowned Centre of Excellence run jointly by TU Berlin, Free University, Humboldt University, Zuse Institute, and Weierstrass Institute, in which nearly 200 scientists pursue application-oriented and theoretical research.
The mostly application-oriented research at the Institute of Mathematics is based on the orientation of the existing workgroups:
- Discrete and Algorithmic Mathematics
- Stochastics and Financial Mathematics
- Geometry and Mathematical Physics
- Modelling, Numerics, Differential Equations
The departments' research is characterised by a plurality of third-party-funded projects, especially within the network of Mathematics at Berlin and in cooperation with other natural and engineering sciences. With its research accomplishments, the Department for Mathematics earns leading positions in national and international rankings.
The faculty member Professor Volker Mehrmann is a member of the National Academy of Science and Engineering (acatech).
TU Delft
The programme is a special track of the Applied Mathematics master's programme run by the Delft Institute of Applied Mathematics (DIAM). DIAM is the largest mathematics research and education group in The Netherlands. DIAM consists of six sections: Numerical Analysis, Mathematical Physics, Analysis, Applied Probability, Statistics and Optimization. Within these sections, a broad range of topics is covered, from applied to pure mathematics. The research in DIAM is also embedded in the following larger initiatives:
- TU Delft Institute for Computational Science and Engineering
- Powerweb
- Multi-Objective Design Optimisation of Fluid Energy Machines (supported by the EU programme Horizon2020)
The faculty includes Professor Cornelis Oosterlee and Professor Arnold Heeminck.
Numerical Analysis
In the numerical analysis group, the main research directions are: discretisation of partial differential equations, fast and robust (non) linear solvers and High-Performance Computing. Concerning solvers, the TU Delft group is one of the leaders in the field. Some current research topics include: fast solvers for seismic research, computational finance, medical imaging, computational health, Computational Fluid Dynamics, High-Performance Computing, Power Grid simulations, and Computational Physics.
Mathematical Physics
In Mathematical Physics, research is done on the modelling of various physical phenomena and a combination of these models with High-Performance Computing. Research topics are: data assimilation, simulation of transport processes, high-performance computing, differential equations and asymptotics, and stochastic differential equations.
Optimisation
Within the Optimisation Section, the following topics are covered: mixed integer linear programming, convex geometry and optimisation, combinatorial optimisation, semidefinite programming, discrete and computational geometry, geometry of lattices, and algorithms and complexity.