Postdoctoral Researcher at Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Saxony, Germany
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Summary
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Oliver Contier is a cognitive and computational neuroscientist with nine years of experience probing how the human brain represents a complex, dynamic world using advanced fMRI and neuroimaging methods. Currently a postdoctoral researcher at Justus Liebig University Giessen and research scientist at the Max Planck Institute for Human Cognitive and Brain Sciences, he blends experimental design, statistical analysis, and computational modeling to map perception and cognition onto brain activity. His PhD training in the Max Planck School of Cognition and hands-on internships (including a summer at James Haxby’s lab) underpin a strong track record in fMRI studies of face familiarity, learning, and music-evoked plasticity. Beyond academia, he contributes to open-source neuroimaging tooling—improving preprocessing workflows in the widely used nipype project—demonstrating attention to reproducible pipelines and robust code. Based in Leipzig, Germany, he combines deep domain knowledge with practical software contributions that make large-scale neuroimaging analyses more reliable.
9 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS Psychologie, Bachelor of Science - BS Psychologie at Universität Trier
Master of Science - MS Psychologie, Master of Science - MS Psychologie at Otto-von-Guericke University Magdeburg
Max Planck School of Cognition, Max Planck School of Cognition at Max Planck Society
Doktor (Dr. rer. nat.) Psychologie, Doktor (Dr. rer. nat.) Psychologie at Leipzig University
Workflows and interfaces for neuroimaging packages
Role in this project:
Backend Developer
Contributions:7 commits, 5 PRs, 1 comment in 3 years 2 months
Contributions summary:Oliver primarily contributed to the `nipype` repository by adding new functionalities and fixing code related to the preprocessing workflows for neuroimaging data. They enhanced the `create_featreg_preproc` function by allowing selection of the reference run using strings and integers. The user also added rudimentary tests and made adjustments to the `pickrun` function to handle single file names and various selection methods. These changes involved modifications to existing Python code and the addition of corresponding tests.
Contributions:56 pushes, 1 branch in 8 years 1 month
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