Florian Jehn
Postdoctoral Teaching Fellow at SoDy
Gießen, Hesse, Germany
Summary
👤
Senior🎓
Top SchoolFlorian Jehn is an environmental data scientist and postdoctoral teaching fellow with nine years of experience applying data science and computational modelling to climate change, hydrology, food security and existential risks. He designs and teaches novel courses on global catastrophic risk while leading interdisciplinary research at organizations like ALLFED and SoDy, translating complex simulations into actionable policy and response plans. Florian has contributed to open-source scientific tooling (notably back-end improvements to the spotpy parameter‑optimization library) and emphasizes robust, well-documented research code. His work spans rigorous bibliometric and living literature reviews to spatial analyses of resilient food systems—an unusual blend of hands‑on modelling, pedagogy and public-facing synthesis. Trained to the doctorate level in hydrology, he combines field-rooted environmental insight (and an earlier apprenticeship as a winemaker) with a clear focus on communicating and operationalizing high-stakes research.
9 years of coding experience
6 years of employment as a software developer
Apprenticeship, Wine Maker, Apprenticeship, Wine Maker at Professional School RheingauDr. rer. nat., Hydrology and Water Resources Science, Dr. rer. nat., Hydrology and Water Resources Science at Justus Liebig University Giessen
German, English
Github Skills (9)
algorithm10
algorithms10
parameter-tuning10
python10
optimisation10
numpy10
optimization10
statistical-models9
data-analysis8
Programming languages (7)
Github contributions (5)
thouska/spotpy
Dec 2017 - Nov 2019
Role in this project:
Back-end Developer
Back-end DeveloperContributions:26 commits, 18 PRs, 24 comments in 1 year 11 months
Contributions summary:Florian primarily contributed to the core functionalities of the `spotpy` library, a statistical parameter optimization tool. Their work focused on adding and modifying parameters within the algorithm implementations (ABC, Fast, FSCABC, MLE, Rope, SA), and correcting a type error in a file. The commits involved modifying algorithm initialization and method signatures. They also contributed to improving the code, by adding a random state variable and fixing the calculation of some signatures.
optimizationstatisticalmachine-learningparameterparameter-estimation
allfed/ALLFED-matplotlib-style-sheet
Oct 2022 - Feb 2025
Style sheet for Python
Contributions:12 PRs, 14 pushes, 1 branch in 2 years 4 months
csssheetpythonstyle-sheet
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.