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Translational Integration for Neuroimaging Data Science adsa
20: Biological Engineering
Our lab develops advanced data science techniques for translational neuroimaging, in order to integrate insights across species for next-generation psychopharmacological applications. As part of this project you have the opportunity to get hands-on experience with cutting-edge toolkits, data repositories, and innovative machine learning applications. The core question of your work would be how brain region matching can best be optimized between species, using image features and reference parcellation atlases. Your work will consist in interfacing with reference database application programming interfaces, sourcing parcellation atlases, and processing neuroimaging data sourced from multiple labs. Additionally, you will test workflow capabilities for multiple model animal species and further our work on rat data standardization. The software environment most relevant for your work will be SciPy (scipy+numpy+pandas) and nipy (nipy+nipype+nibabel).
To adequately tackle the challenges of this project you should have: • some previous experience working on Linux • previous experience and confidence coding in Python • a keen interest in neuroscience, psychopharmacology, open science, and data standardization Though not mandatory or assumed, the following would be a significant plus: • prior experience with web APIs such as the one of the Allen Brain Institute • prior experience with Git • prior experience with MRI or other volumetric data • prior experience with the Gentoo Linux distribution