Master´s projects

Our Group offers Master´s thesis projects in the following areas:

Cesare Franchini

Computational and theoretical studies of materials properties at quantum level using advanced
electronic structure methods, diagrammatic quantum Monte Carlo, spin Hamiltonians, and artificial intelligence. Current thesis topics: (i) polaron quasiparticles; (ii) entanglement between spin, orbit, lattice and electron correlation; (iii) computational surfaces  including reconstructions, polarity, topology and adsorption. The research can involve both application of existing packages or code development and are often conducted in collaboration with experimental groups. The Master student (m/f/d) will be integrated in a friendly research group and will actively participate in discussions, seminars and, if needed, short internships with foreign collaborators.

Kerstin Hummer

Ab-initio modeling of electronic and optical properties of semiconductors using density functional theory (DFT) and many-body perturbation theory, with particular focus on low-dimesional layered materials. Current research questions address band-gap engineering and tailoring the electronic and optical properties of semiconductors by low-dimensional structuring. These investigations are performed using existing computer codes. Research-oriented Master projects for students of the teacher's training program in Physics (MEd) can be offered as well.

Georg Kresse

Our group develops the Vienna ab initio simulation package (VASP). This code is used by more than 3000 research groups worldwide. Current research includes developments to solve the one-particle Schrödinger equation for solids, quantum Monte Carlo methods to solve the many-body Schrödinger equation, and machine learning methods to accelerate the computation of material properties. We also apply the developed methods to a variety of condensed matter problems of current interest, including energy materials and problems in surface sciences and catalysis. Master's student projects can cover any of the current research areas and typically involve some coding, for example using Python. However, most Master's projects are more applied and involve computations with existing computer codes, such as VASP.

Anatole von Lilienfeld

Within the Lilienfeld-lab we study trends and relationships in chemical compound space using ab initio and machine learning methods. Our research serves the ultimate goal to rigorously design or discover novel materials on a computer. Employed electronic structure methods include density functional theory, post-Hartree-Fock methods, and Quantum Monte Carlo. Phase space is sampled using molecular dynamics, Monte Carlo, and path-integrals. Extrapolations and interpolations in compound space are typically performed with alchemical perturbation theory and support vector machines, respectively. Specific Master projects are determined within preliminary discussions with the professor, and typically require extensive programming.