Jonas Glombitza
Postdoctoral Researcher at Friedrich-Alexander-University of Erlangen-Nürnberg
Erlangen, Bavaria, Germany
Summary
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Senior🎓
Top SchoolJonas Glombitza is a postdoctoral researcher at the Erlangen Centre for Astroparticle Physics with nine years of experience applying deep learning to gamma-ray and ultra-high-energy cosmic-ray physics. He leads the machine learning task within the Pierre Auger Collaboration and has developed CNN, RNN, transformer and graph-based methods for particle reconstruction, simulation acceleration and domain adaptation. Proficient in Python and libraries such as TensorFlow, PyTorch and PyTorch Geometric, he bridges advanced ML research with hands-on implementation and teaching, having lectured "Deep Learning for Physics Research" and coauthored a related book. His work includes international research stints at Berkeley Lab and the University of Maryland, reflecting a collaborative, cross‑institutional profile. Colleagues note his blend of statistical rigor, self-organization, and a knack for turning complex detector data into tractable ML problems.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at RWTH Aachen University
English, German, French
Github Skills (7)
physics9
machine-learning9
deep-learning9
iml6
python5
generative-adversarial-network3
pytorch2
Programming languages (2)
Github contributions (5)
jglombitza/tutorial_graph_networks
Feb 2020 - Feb 2021
Contributions:13 commits, 14 pushes, 1 branch in 1 year
jglombitza/tutorial_generative_models
Mar 2021 - Mar 2022
Contributions:10 commits, 8 pushes, 2 branches in 1 year
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