Axel Pahl
Medicinal Chemist Chemical Data Scientist
Hannover-Braunschweig-Göttingen-Wolfsburg Region Germany
Summary
👤
Senior🎓
Top SchoolAxel Pahl is a medicinal chemist turned chemical data scientist with 11+ years of experience applying organic and medicinal chemistry to bacterial anti-virulence targets while building robust data pipelines and virtual screening workflows. He combines hands-on bench expertise from industry and academia with strong programming skills in Python and Rust, plus database design (PostgreSQL) and cheminformatics tooling (RDKit, Pandas, KNIME). A contributor to the flagship RDKit project, Axel has improved cross‑platform compatibility and visualization features, reflecting a rare blend of domain science and open-source engineering. Based between Hannover and Hamburg, he currently advances computational chemistry at Fraunhofer ITMP after nearly a decade at the Max‑Planck Institute working on Cell Painting and COMAS. Notably, he pairs practical drug discovery experience (MRSA virulence inhibitors) with Linux/automation fluency to accelerate reproducible virtual screening and data-driven medicinal chemistry.
11 years of coding experience
21 years of employment as a software developer
Promotion, organische Chemie, Promotion, organische Chemie at Universität Hannover
English
Stackoverflow
13reputation
31reached
0answers
1question
Github Skills (12)
compatible10
rdkit10
cross-platform10
multiplatform10
python10
cheminformatics10
cprogramming-language9
pandas9
c-language9
api8
apidoc8
altair6
Programming languages (18)
Github contributions (5)
rdkit/rdkit
May 2015 - Oct 2017
The official sources for the RDKit library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 9 commits, 12 PRs in 2 years 6 months
Contributions summary:Axel primarily focused on enhancing the RDKit library's functionality, particularly concerning cross-platform compatibility and feature additions. They addressed Python 2/3 compatibility issues by modifying import statements and integrating `cairocffi` for Python 3. Furthermore, the user implemented new features, such as adding `showSticks` to the `ShowMol` method, and refactored modules to improve their usability and importability, such as the SAScorer and NPScore modules. The contributions also include modifications to the PandasTools module to improve the DataFrame visualizations.
cheminformaticsrdkitpythonc-plus-plussources
apahl/nim_magic
Jun 2018 - Apr 2022
Contributions:8 commits, 3 pushes, 1 branch in 3 years 10 months
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