Tomas Stolker

Assistant Professor at Leiden University

Amsterdam, North Holland, Netherlands
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Summary

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Senior
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Top School
Tomas Stolker is an Assistant Professor and Veni fellow at Leiden University with 10 years’ experience leading observational programs to directly detect and characterize exoplanet atmospheres. Trained as an astrophysicist at the University of Amsterdam, he combines image processing from premier telescopes with atmospheric retrievals, statistical inference, and machine learning to extract faint planetary signals from large, noisy datasets. His postdoctoral work at ETH Zürich refined high-contrast imaging and modeling techniques now applied to multi-instrument surveys. Tomas is as comfortable writing atmospheric retrieval code as he is designing observing strategies, and he often bridges instrument teams and data scientists to turn complex raw data into robust physical constraints. Based in Amsterdam, he brings academic rigor and hands-on computational skill to push the frontier of extrasolar planet characterization.
code10 years of coding experience
job7 years of employment as a software developer
bookMaster of Science - MS, Astronomy and Astrophysics, Master of Science - MS, Astronomy and Astrophysics at University of Amsterdam
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Github Skills (64)

high-contrast10
image-processing10
carbon-emissions10
imaging10
hpc-applications10
climate-change10
masking10
pipeline10
orbit10
contrast10
reduction9
python9
orbital-mechanics9
extraction9
instrumentation9

Programming languages (5)

TypeScriptCJupyter NotebookPythonFortran

Github contributions (5)

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tomasstolker/skycalc_ipy

Oct 2021 - Dec 2024

iPython version of skycalc_cli
Contributions:12 pushes, 1 branch in 3 years 2 months
ipythonpythoncli
tomasstolker/specutils

Apr 2021 - Mar 2025

An Astropy coordinated package for astronomical spectroscopy. Maintainers: @nmearl @crawfordsm @keflavich @eteq
Contributions:11 pushes, 2 branches in 3 years 11 months
astrophysicsorbitastropyastronomymaintainers
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Tomas Stolker - Assistant Professor at Leiden University