Programme structure

Outline

The structure of the programme is flexible in order to increase your opportunities to tailor your studies to your own interests, which means that some courses may be offered across several different semesters. As a result, the course list below does not always provide a complete picture of the semester in which you will study a specific course.

During your studies, you will take at least 22.5 credits elective courses, which must include one of the following courses: Electromagnetism, Nuclear Physics or Particle Physics, Cosmology and Accelerators and at least two of the following courses:

• Computational Science: Reproducible Data Science and Statistical Learning
• Computational Science: Introduction to Artificial Neural Networks and Deep Learning
• Computational Science: Uncertainty Quantification & Data-driven Modelling
• Computational Science: Parallel Programming in Scientific Computing
• Physics: Quantum Computation
• Mathematical Statistics: Monte Carlo Methods for Statistical Inference
• Numerical Analysis: Advanced Course in Numerical Algorithms with Python/SciPy
• Numerical Analysis: Numerical Simulations of Flow Problems
• Numerical Analysis: Numerical Methods for Partial Differential Equations

In addition, you will take 30 credits elective courses. The elective courses should be chosen so that, in total from compulsory, alternative-compulsory and elective courses, you will take at least 30 credits of advanced-level physics courses and 30 credits of advanced-level courses in computational science.