DFT is routinely used for computational investigations of molecules and materials, including semiconductor defects for quantum sensing. Key challenges include the development and testing of more accurate density-functional approximations, as well as many-body models that go beyond standard DFT. Machine learning approaches and traditional analytical (“pen-and-paper”) development go hand in hand with software development, including advanced visualization approaches, in this area.
Prerequisite knowledge:
Recommended courses to take during first semesters of master programme: