Scientific Intern

March 2023 - ongoing
Scientific Intern at the Institute of Science and Technology Austria
under supervision of Prof. Bingqing Cheng

• Machine learning applications for Computational Material Sciences
• Building a machine learning framework for modeling thermodynamic properties of materials
• Methods: Gaussian Process Regression, Molecular Dynamics, Density Functional Theory
• Technologies: Python, JAX - Differentiable programming
  
  

January 2023 - February 2023
Project Intern at the Technical University of Vienna
under the supervision of Prof. Jan Kunes

• A study of DC optical conductivity in ferromagnetic SrCoO₃
• Methods: Density Functional Theory
• Technologies: WIEN2K, Python
  
  

March 2020 - June 2021
Project Intern at the Technical University of Vienna
under the supervision of Prof. Karsten Held and Univ. Ass. Anna Kauch

• Modelling properties of Mott insulators via Hubbard clusters
• Study impact ionization in Hubbard clusters, and use Hubbard clusters as a model for Mott Transistors
• Methods: Exact diagonalization, Hubbard model
• Technologies: C, Python, Vienna Scientific Cluster
  
  

September 2019 - October 2022
Master programme Technical Physics at the Technical University of Vienna
Dipl. Ing. (equivalent to M.Sc.)

• Master Thesis: Group equivariant neural networks for a scalar field theory
  • under the supervision of Prof. Andreas Ipp
  • Links Code (GitHub), Thesis
  • Methods: Machine Learning, Neural Networks, Group Theory
  • Technologies: Python, Pytorch, Optuna
• Graduated with distinction
  
  

September 2016 - September 2019
Bachelor programme Technical Physics at the Technical University of Vienna
B.Sc.

• Bachelor Thesis: Characterization of a Single Molecule Fluorescence Microscope
• graduated with distinction