Master in Computational Science, Scientific Computing

Lund University, located in Lund, Sweden, is a historic institution founded in 1666. You'll find many advantages to studying here, including access to cutting-edge research facilities, a strong international profile with partner universities in 75 countries, and excellent conditions for scientific breakthroughs and innovations. As a student, you'll be part of a large and diverse community with 45,000 students, including 12,600 international students.

The university focuses on many subjects, including economics and management, engineering and technology, fine arts, music and theatre, humanities and theology, law, medicine, science, and social sciences. With 147 programs available, you can choose from a broad range of fields. Specifically, the university is home to two world-leading research facilities, the synchrotron radiation facility MAX IV and the European Spallation Source (ESS), which will be fully operational by the end of 2027.

As a student at Lund University, you'll have access to modern facilities and a unique location. The city of Lund offers a great quality of life, with opportunities to engage in cultural and social activities. For instance, the university's commitment to creating an international hub for research, education, and innovation provides a dynamic environment for you to grow and learn. You'll be able to take advantage of the university's strong industry partnerships and collaborations, making it an ideal place to study and launch your career.

The Master in Computational Science, Scientific Computing at Lund University is a 2-year program that gives students specialized knowledge about methods used in computational science and how to apply them. This Master's degree program is taught in English and focuses on numerical simulations and machine learning to make forecasts and analyses.

The curriculum emphasizes mathematics, numerical analysis, and mathematical statistics. The course design combines numerical methods for differential equations with mathematical statistics and natural sciences to provide students with knowledge and skills for differential equation-based and data-based modeling. Courses include modeling in computational science, Monte Carlo methods for statistical inference, and artificial neural networks.

Graduates of this program can pursue careers as Scientific Computing Specialist, Data Analyst, Computational Scientist, Research Scientist, or Software Engineer. They can work in industries such as research, finance, or technology, and can be employed by organizations such as NASA, Google, or IBM.