Studies

The Computational Materials Physics group at the University of Vienna offers teaching across all stages of academic study, from Bachelor to PhD level.

Bachelor’s Programmes

In the Bachelor’s programmes, students develop a solid foundation in physics and mathematics, while gaining first experience with computational methods.

Courses offered within the Computational Materials Physics group:

• Preparation course STEOP 2 260040 (for Bachelor students)
  The course is designed to support first-year students in the Bachelor Physics/Astronomy/Meterology and Climate Science programs in independent learning in preparation for the StEOP2 module exam.

• Scientific Computing 260091 (for Bachelor students)
  Introduction to numerical methods for solving physical problems

• Data Science for Physicists 260072 (for Bachelor students)
  Basic concepts of data analysis, statistics, and machine learning in physics

• Bachelor Seminar 260080 (for Bachelor students)
  This course allows students to write a bachelor's thesis as part of the curriculum.

• Mathematical Methods 2 267301 (for Bachelor students)
  Aneignung der für das Lehramtsstudium Physik wesentlichen mathematischen Werkzeuge und Konzepte aus Analysis und Linearer Algebra, die für den Aufbau eines fundierten Konzeptwissens in der Physik in allen weiteren Modulen im Studienverlauf notwendig sind.

Master’s Programmes

At the Master’s level, students specialize in areas such as quantum-mechanical simulations, materials modelling, and advanced numerical methods.

Course offered within the Computational Materials Physics group:

• Advanced Electronic Structure 260064 (for Master students)
  In-depth study of modern electronic structure theory and its application to complex materials

• Surfance Science 260046 (for Master students and PhD Students)
  The course aims to introduce Master and PhD Students to fundamental aspects of Surface Science.

• Introduction to Computational Chemistry and Physics 262010 (for Master students)
  The lecture is dedicated to master students in computational science with a background in mathematics and informatics, as well as master students of material chemistry. 

• Machine Learning in Computational Physics 260063   (for Master students)
  The aim of this course is to provide students with a practical and conceptual understanding of how machine learning techniques can be applied to problems in computational physics.

PhD / Doctoral Programme

The doctoral programme focuses on independent research. Students contribute to ongoing projects in computational materials physics, including the development of new materials and computational approaches.

Study Path

The programmes form a continuous progression:
from foundational training → to specialization → to independent research in computational materials physics.