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🌟 Core Competencies
From my background in physics and computational science, I have a strong foundation in using numerical methods and statistical methods for solving physical problems. Examples of such methods include numerical methods for differential equations, Monte Carlo simulations, statistical learning including Bayesian methods and machine learning, both supervised and unsupervised approaches.
I am particularly interested in using those skills for peaceful applications of nuclear science. My bachelor degree thesis was about applying machine learning on radioactive decay data. I am proficient in Python, experienced with R and MATLAB, and have some exposure to C++, C# and SQL. I am very comfortable with GNU/Linux and Git workflows.
My master degree thesis will be on furthering the development of a Bayesian algorithm for multisource detection in mobile gamma spectroscopy.
{{< notice tip >}}A selection of code can be found on my git instance.{{< /notice >}}
🧪 Workshops & Summer Schools
I like to attend summer schools and (online) workshops in order to broaden my knowledge or refresh some old skills. Below is a timeline of selected workshops which I have followed in the past.
Modern Python in Depth
Leibniz Supercomputing Centre, Germany 🇩🇪
Online workshop.
Scientific computing Modern Python standard
Core Modeling For Core Design
GRE@T-PIONEeR @ Chalmers University of Technology, Sweden 🇸🇪
One week course on-site at Chalmers. Learned the principles of probabilistic and deterministic methods for steady-state core modelling, applied to reference calculations, operations and safety analysis.
Reactor physics Nuclear engineering
ENEN2+ Nuclear Summer School
Budapest University of Technology and Economics, Hungary 🇭🇺
Participated in a week summer school at the BME Training reactor in Budapest, on scholarship from the European Nuclear Education Network. Experiments were focused on the principles of reactor physics; determining neutron flux, criticality experiments, and operations.
Reactor physics Experimental physics
High-performance Computing with Python
Jülich Supercomputing Centre, Germany 🇩🇪
Online workshop.
HPC
Parallelization Scripting
Intermediate Bash and Linux
HPC2N, Umeå University, Sweden 🇸🇪
Online workshop.
grep Sed and AWK Bash scripting
Bayesian Statistical Learning
Jülich Supercomputing Centre, Germany 🇩🇪
Online workshop.
MCMC PyMC3 Supercomputer usage
Programming with Fortran
Leibniz Supercomputing Centre, Germany 🇩🇪
Online workshop.
Arrays Subroutines Derived Types I/O Performance considerations
Code & Collaborate: The FAIRytale of Software Development
EPFL CECAM & BioNT, Switzerland 🇨🇭
Online workshop.
Git (CLI) Continuous Integration Code Documentation