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Computational and data Science Synergy Track

Data science and computational methods play an increasing important role in modern science as well as in industry and society. We offer a synergy track Computational and Data Science in the master Physics and Astronomy and use the synergy of different disciplines in the science faculty that are engaged in computational modeling and data science.

This track consists of 15 EC and intersects with the existing specialisations in the physics master (particle and astrophysics, physics of molecules and materials, neurophysics), physical chemistry and mathematics.

The common base consists of 3 courses (3 EC), that cover fundamental aspects of computing and data science independent of chosen specialisation direction:

Depending on the chosen specialisation, students can extend this programme based on their interests:
Physics of Molecules and Materials
Quarter 1
NWI-SM297 Molecular Modelling (3 EC)
Quarter 2
NWI-MOL406 Quantum Chemistry (3 EC)
NWI-SM299 Pattern Recognition for Natural science (3 EC)
Quarter 4
NWI-SM295 Quantum Dynamics (3 EC)
Particle and Astrophysics
Quarter 1
NWI-NM042B Monte Carlo Techniques (6 EC)
Quarter 2
NWI-NM067B Data analysis (3 EC)
Quarter 3
NWI-NM121 Astronomical Instrumentation & Data Analysis (6 EC)
NWI-NM116B Machine Learning in Particle Physics and Astronomy (6 EC)
Quarter 4
Quarter 2
NWI-NM048B Advanced Machine Learning (6 EC)
NWI-NM047D Computational Neuroscience (3 EC)
Quarter 3
NWI-IMC030 Machine Learning in Practice (6 EC)
NWI-NM127 Modelling of Complex Real-world Systems (6 EC)