Jonas Eschle
Quantitative Researcher
Geneva, Geneva, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolJonas Eschle is a senior applied fellow at CERN with a decade of experience combining large-scale software engineering, statistical methods, and machine learning for high-energy physics. He holds a PhD in Physics from the University of Zurich and has driven research and production-quality contributions—from weighted-histogram support in TensorFlow Probability to expanding Python package coverage in the widely used spack package manager. Comfortable in both research and engineering contexts, he bridges rigorous statistical modelling with practical tooling for scientific computing. Outside academia he has served in leadership roles in volunteer fire services, reflecting a calm, team-oriented approach to high-pressure situations.
10 years of coding experience
2 years of employment as a software developer
Aircraft Pilot (Private), Aircraft Pilot (Private) at FGZODoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of Zurich
German, English, French, Russian
Github Skills (13)
statistics10
machine-learning10
probabilistic-programming10
tensorflow10
package-management10
python10
scientific-computing10
data-science9
build-tools9
package-manager9
package-manager-tool9
numpy8
bayesian-methods7
Programming languages (19)
Github contributions (5)
spack/spack
Aug 2023 - Nov 2025
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:41 reviews, 22 PRs, 106 comments in 2 years 4 months
Contributions summary:Jonas's primary contributions involve adding and updating Python packages within the `spack/spack` repository, a package manager for scientific computing. They focused on incorporating new Python packages like `py-dotmap`, `py-jacobi`, and interfaces such as `py-zfit-interface`. The user also upgraded TensorFlow Probability and adjusted dependencies for various packages to ensure compatibility and functionality. These modifications and additions are key to expanding the capabilities of the package manager.
compilerpackage-managerpythonspackhpc
tensorflow/probability
Oct 2020 - Sep 2022
Probabilistic reasoning and statistical analysis in TensorFlow
Role in this project:ML Engineer
ML EngineerContributions:11 commits, 10 PRs, 50 comments in 1 year 11 months
Contributions summary:Jonas primarily contributed to the `tensorflow/probability` repository by implementing and refining functionality related to the `histogram` function within the `stats` module. Their work involved adding support for weighted histograms, updating documentation to reflect these changes, and ensuring the correctness of the implementation through unit tests. The user focused on expanding the existing statistical tools within the library.
probabilistic-reasoningtensorflowbayesian-methodsdeep-learningmachine-learning
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