Since 2023, the Faculty of Science at Lund University offers a cross-disciplinary master's programme in computational science (maths.lu.se). Currently the programme has three different specializations for students with backgrounds in mathematics, physics or geosciences. For students from less mathematics-heavy sciences such as biology, there is a master's programme in applied computational science (maths.lu.se).

Teaching staff at CEC are involved in the computational science education, including the ongoing development of new paths and possibilities for students. We currently offer three advanced-level courses in computational science. These courses are taught by staff at Computational Science in Health and Environment (COSHE) and have evolved from courses that were previously labeled as theoretical physics.

The computational science courses at CEC are (with links to Canvas):

• Introduction to Artificial Neural Networks and Deep Learning (BERN04/EXTQ41), 7.5 credits – autumn, second study period.
• Theoretical Biophysics (BERN05/EXTQ01), 7.5 credits – spring, first study period.
• Systems Biology – Models and Computations (BERN06), 7.5 credits – spring, second study period.

Courses in computational science have course codes that begin with "BERN" (for beräkningsvetenskap, advanced level). Two of these courses are also available to students at the Faculty of Engineering ("EXTQ" course codes). PhD students are also welcome to take the courses and are adviced to contact the respective course coordinator.

The other computational science courses at the Faculty of Science are currently:

• Modelling in Computational Science (BERN01), 7.5 credits – spring, first study period, at the Centre for Mathematical Sciences.
• Reproducible Data Science and Statistical Learning (BERN02) (kemi.lu.se), 7.5 credits – autumn, first study period, at the Department of Chemistry.
• Introduction to Modelling of Climate System (BERN03) (geology.lu.se), 7.5 credits – autumn, second study period, at the Department of Geology.