Valentin Druelle
Scientific Software Developer at Genedata
Basel, Basel-City, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolValentin Druelle is a scientific software developer and PhD-trained bioinformatician with six years of cross-disciplinary experience building data-driven R&D tools for life sciences. He blends software engineering, automation and wet-lab expertise—having designed an autonomous bacteriophage evolution machine and established a high-throughput Nanopore sequencing facility processing 200+ samples monthly. His work spans end-to-end pipelines (>1TB, HPC), deep learning models for genomics, and practical device engineering (CAD, embedded systems, custom sensors). Valentin contributed to prominent open-source COVID-19 modeling efforts, improving R0 estimation and fitting procedures used for outbreak scenario projections. He excels at translating biological questions into robust, automated workflows that accelerate discovery and has a track record of mentoring students into top programs. Based in Basel, he combines rapid learning with hands-on collaboration to deliver impactful, production-ready solutions.
6 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Bioinformatics, Doctor of Philosophy - PhD, Bioinformatics at Biozentrum, University of BaselMaster of Science - MS, Physics Engineering, Numerical physics, Biophysics, 5.81, Master of Science - MS, Physics Engineering, Numerical physics, Biophysics, 5.81 at EPFL (École polytechnique fédérale de Lausanne)
French, English, German
Github Skills (11)
data-visualizations10
pandas10
data-visualization10
data-visualisation10
python10
data-analysis10
co9
covid-testing9
scipy9
vi9
machine-learning8
Programming languages (3)
Github contributions (5)
neherlab/covid19_scenarios
Apr 2020 - Jun 2020
Models of COVID-19 outbreak trajectories and hospital demand
Role in this project:
Data Scientist
Data ScientistContributions:74 commits, 2 PRs, 36 pushes in 2 months
Contributions summary:Valentin's contributions centered around modifying and improving a COVID-19 outbreak trajectory model. They refactored data loading procedures to select relevant regions for fitting and separated data loading from the selection process. The user also implemented a new fitting procedure, including the use of a stair function to model R0 changes and a Poisson maximum likelihood cost function, demonstrating a focus on enhancing the model's accuracy and functionality. They have been working on the comparison of the R0 estimations.
hospitaldatancovoutbreakscience
vdruelle/Aionostat_code
Mar 2023 - Jan 2025
Code to run the morbidostat for my phage experiments.
Contributions:1 PR, 46 pushes, 2 branches in 1 year 10 months
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