Dániel N.
Postdoctoral Researcher - Theoretical and Computational Physics
Experience
Jan 2022 - Dec 2025
4 yearsNijmegen, Netherlands
Postdoctoral Researcher - Theoretical and Computational Physics
Radboud University
- Built and maintained C and C++ simulation engines with Python analysis for studies of 4D random geometries on shared HPC systems.
- Developed modular Python pipelines with clear interfaces and caching for large datasets to improve analysis throughput and reuse.
- Automated SLURM and PBS batch workflows for submission, monitoring, environment capture, and artifact packaging to ensure reproducibility.
- Refactored utilities into tested, documented packages to lower maintenance effort and support collaboration.
- Supervised BSc students and organized seminars.
- Published several peer-reviewed papers.
Jan 2018 - Dec 2022
5 yearsKraków, Poland
PhD Researcher - Theoretical Physics
Jagiellonian University
- Implemented Monte Carlo engines in C and C++ for simplicial lattice quantum gravity with Python diagnostics and Mathematica visualization.
- Wrote tools for parameter sweeps, logging, checkpointing, and resume for long runs across clusters.
- Added sanity checks, invariants, and regression tests for earlier detection of numerical issues and safer datasets.
- Co-authored 10+ peer-reviewed publications and presented results at international conferences.
Summary
Computational physicist with 7+ years in large scale numerical simulations, data analysis, and scientific software. Strong in C and C++, Python, and reproducible HPC workflows. Experienced with Monte Carlo methods, random geometries, and geometric observables. Open to industry R&D and data driven engineering roles.
Skills
- Programming: C And C++, Python, Bash, Git, Cmake, R
- Machine Learning: Pytorch, Tensorflow, Keras, Xgboost, Scikit-learn, Graph And Simplicial Neural Networks
- Computing: Hpc Clusters (Pbs, Slurm), Parallel And Batch Workflows, Profiling, Numerical Optimization
- Practices: Unit And Regression Tests, Code Review, Continuous Integration, Documentation
- Monte Carlo Simulation Framework: Modular C And C++ Engines For Large Scale Monte Carlo On Hpc Clusters Using Link-cut Trees For Dynamic Connectivity, Pluggable Field Modules, And Robust I/o
- Data Analysis Toolkit: Python Command Line Tools For Descriptive Statistics, Sanity Checks, Function Fitting, And Plots With Stable Defaults And Documented Flags; Supports Csv, Numpy, Pickle, And Hdf5 Formats With Export To Pdf And Png
- Spectral Analysis Toolkit: Parsers And Adapters That Extract Incidence Matrices And K-simplicial Laplacians From Run Outputs, Building Sparse Multi-dimensional Operators And Supporting Batch Mode With Numpy, Scipy Sparse, And Hdf5 Formats
- Mathematica Visualization Framework: Notebooks And Functions For 2d And 3d Geometry Including Mesh Rendering, Parametric And Surface Plots, Interactive Controls, And Batch Export To Pdf And Png
- Hpc Workflow Utilities: Bash Templates For Job Submission On Different Hpc Setups, Monitoring, Environment Capture, And Artifact Packaging For Reproducible And Transferable Workflows
Languages
Hungarian
NativeEnglish
AdvancedGerman
IntermediatePolish
ElementaryEducation
Oct 2018 - Jun 2022
Jagiellonian University
PhD in Theoretical and Computational Physics · Theoretical and Computational Physics · Kraków, Poland
Oct 2016 - Jun 2018
Eötvös Loránd University
MSc in Physics, Astronomy module · Physics, Astronomy module · Budapest, Hungary
Oct 2012 - Jun 2016
Eötvös Loránd University
BSc in Physics, Theoretical module · Physics, Theoretical module · Budapest, Hungary
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