about
Jonas GreitemannComputational physicist
I’m passionate about writing clean, scalable code which follows the principle of zero-cost abstraction, combining the readability and safety of a high-level language with the bare-metal efficiency of a systems language. Until recently, I did so as part of my physics doctorate where I quickly built a reputation among colleagues for my advice in all matters C++.
I strive to continuously broaden my horizons, be it by adopting best practices, trying novel language features (C++20), or learning about emerging tech (Rust, WebAssembly) and agile workflows.
Skills
Experience
Software Architect C++ at MVTec
since 12/2019
MVTec Software GmbH
Research Scientist at LMU Munich
10/2015 – 8/2019
Development of a machine learning framework for the recognition of unconventional magnetic phases in Monte Carlo simulations of frustrated spin systems. This entails the characterization of so-called spin liquids and types of spin order which exhibit multipolar moments rendering them invisible to conventional numeric probes—“hidden order”. The method relies on a combination of support vector machines and spectral graph theory.
Education
Doctoral studies at LMU Munich
until 2019
Chair for theoretical nanophysics; advisor: Prof. Dr. Lode Pollet
Thesis: Investigation of hidden multipolar spin order in frustrated magnets using interpretable machine learning techniques
Springorum Commemorative Coin
2016
Master of Science (Physics) from RWTH Aachen
2015
Institute for theoretical solid state physics; advisor: Prof. Stefan Wessel, PhD
Master's thesis: Quantum Monte Carlo investigation of the one-dimensional Hubbard-Holstein model — Implementation and optimization of a highly parallel Monte Carlo simulation; extensive numerical studies at the Jülich Supercomputing Centre (0.5M CPU-hrs.)
Bachelor of Science (Physics) from RWTH Aachen
2013
Institute for theoretical solid state physics; advisor: Prof. Stefan Wessel, PhD
Bachelor's thesis: Stochastic Analytic Continuation — Implementation of an optimization algorithm (in C++) for solving the inverse problem inherent to the reconstruction of spectral functions from quantum Monte Carlo simulation data