Resume

Maximilian Böhme

Physics master student

October 2017 - current

Masters degree Physics, Technical University Dresden

Thesis: Investigation of Ionization Potential Depression in Dense Plasmas from Be capsule implosions taken at the NIF and from ${\it ab \, initio}$ simulations
Specialization: Theoretical solid-state physics and Chaos in higher-dimensional system
Minor: Computer science
Expected graduation date: May 2020

October 2016 - August 2017

Masters degree Computational Science and Engineering(not finished), Technical University Dresden and Technical University Freiberg

October 2013 - August 2016

Bachelors degree Physics, Technical University Dresden

Thesis: The Time Dependent Schrödinger Equation in a Strong Laser field, Grade: 1.0
Minor: Computer Science
Final Grade: 2.0

November 2018 - February 2019

Visiting Scholar - University of California Berkeley, Department of Earth and Planetary science

Worked on DFT/DFT-MD simulations to study the effect of ionization potential depression in dense plasmas. Publication is currently in preparation.

August 2018 - February 2019

Summer intern - Lawrence Livermore National Laboratory

Worked on X-Ray Thomson Scattering data taken at the National Ignition Facility

Implemented a $\chi^2$ fitting library for XRTS spectra
Implemented a self-consistent fitting strategy for general XRTS spectra without any special assumptions on the continuum lowering model

November 2017 to Present

Student employee (Remote) - ESTION Technologies GmbH

Maintaining and developing the Data-analysis software for the products E-RETICLE and E-WAFER

September 2014 to Present

Student research assistant - Helmholtz-Zentrum Dresden-Rossendorf

Design and implement scalable high performance simulations using various parallelization libraries on CPUs as well as GPUs on the hypnos HPC cluster
Implementation of a parallel solver for the one-dimensional Time Dependent Schrödinger Equation using NVIDIA CUDA
Implemented high performance simulations of charged particles in electromagnetic fields by using the parallelization libraries OpenMP and OpenMPI
Evaluate several gigabytes of simulation data using Python
Running high performance density functional theory simulations on the TU Dresden Taurus HPC system

Experienced in designing massively parallel simulations on HPC clusters
Familiar with the test driven development cycle and scrum
Proficient in C++-11/14 and Python
Experienced in data-analysis with Python using the established data-analysis libraries Numpy, Matplotlib and Mayavi2
Experienced with Linux cluster usage, this includes experience with workload managers like SLURM or PBS
Proficient in designing and implementing algorithms on GPUs using NVIDIA CUDA
Experienced in designing and parallelizing simulations with OpenMP and/or OpenMPI
Profound experience in using CMake and git
Experienced in using Microsoft Office as well as $\LaTeX$
Hands-on experience with container virtualization using Docker
Essential knowledge of functional programming styles in C++ and Python
Basic knowledge of functional programming using Common Lisp
Basic knowledge of Java and SQL
Some experience with Matlab, Octave
Experienced in maintaining and developing Scilab applications delivered to international customers
Experienced in the usage of HPC density functional theory codes Abinit and CPMD

Statistical description of dense plasmas with methods of linear response theory
Description of ionization potential depression (IPD) under high pressures and extreme compression
Many particle physics in non-equilibrium states
Theory of X-Ray Thomson Scattering (XRTS)
Density functional theory to model dense plasmas and planetary interiors
Numerical solution to partial differential equations, especially the in-medium Schrödinger Equation