Katharina Glomb
Wissenschaftliche Referentin at Bundesinstitut für Risikobewertung
Berlin, Germany
Summary
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Senior🎓
Top SchoolKatharina Glomb is an impact-driven data scientist and scientific advisor with nearly a decade of experience applying computational neuroscience to real-world problems. She has led cross-disciplinary research teams, developed advanced network-analysis methods for EEG and MRI data, and translated complex findings into clear, actionable messages for stakeholders. As a co-founder and lead coordinator of a civic non-profit, she combines grant-writing, community building, and public-speaking experience with rigorous research practice. Currently at the Bundesinstitut für Risikobewertung, she is transitioning her analytical and communication strengths into data science or consulting roles that advance a just, green transition. Known for generating out-of-the-box ideas, she pairs technical depth (PhD in computational neuroscience) with a talent for organizing complexity and coaching teams. Based in Berlin, she brings both academic rigor and grassroots leadership to impact-focused organizations.
9 years of coding experience
6 years of employment as a software developer
Master of Science - MSc, Computational neuroscience, Master of Science - MSc, Computational neuroscience at Technische Universität BerlinPhD, Computational neuroscience, PhD, Computational neuroscience at Universitat Pompeu FabraBachelor of Science - BSc, Biology, Bachelor of Science - BSc, Biology at Humboldt University of Berlin
Github Skills (15)
neuroimaging9
bold9
neuroscience9
visualization8
machine-learning8
bids8
statistics8
python8
singularity7
mri7
decompose6
docker6
nifti5
mapper4
tensorflow2
Programming languages (2)
Github contributions (5)
Katharinski/tensor-pipeline
Nov 2016 - Oct 2017
Contributions:9 commits, 2 PRs, 21 pushes in 11 months
decomposepythonfmritensorflowtensors
Katharinski/connectomemapper3
Apr 2021 - Sep 2022
Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, and resting/state functional MRI processing pipelines, from raw T1 / DWI / BOLD data to multi-resolution brain parcellation with corresponding connection matrices.
Contributions:35 pushes, 3 branches in 1 year 4 months
brainconnectomebrain-parcellationconnectiondiffusion
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