Hire Kasey Z. - AI Engineer - New York

* Perform agglomerative hierarchical clustering using 30 dendritic and axonal morphological features, selected using data-driven feature selection methods, extracted from SWC files of over 2,700 reconstructed cells across 15 cortical regions of the mouse brain to validate subjective cell type labels. Create, fit, and hyperparameter-tune separate random forest classifier models on morphological feature data for each region to standardize and automate the future prediction of cell types for larger data sets. Conduct ANOVA tests for features across cell types to assess statistical significance between brain regions. Generate visualizations using Matplotlib, Seaborne, and Excel (used in Nature manuscript) to compare targeting probabilities and strengths across 6 layers of 10 cell types in 15 cortical regions, as well as plots visualizing how morphological features of these cell types vary across regions. Reconstruct 3D models of somatosensory cortical cells by tracing images of the mouse brain using Vaa3D-Tera Virtual Reality.

* Collected, pre-processed, analyzed, and visualized experimental data (e.g., % accuracy, false alarm rate) using Python and Matplotlib/Seaborn to extract statistical insights, optimizing experimental methods and parameter tuning. * Designed and conducted behavioral contrast detection task experiments on mice, analyzing performance data to evaluate the effects of optogenetic manipulation on neural activity and sensory perception. * Sliced and processed brain tissue samples for histological analysis, ensuring high-quality data and enhanced tissue visibility. * Performed transcardiac perfusions, ensuring optimal brain tissue preservation for accurate data collection and future analysis