Ultracool dwarf stars and brown dwarfs provide a unique probe of large-scale Galactic structure and evolution; however, until recently spectroscopic samples of sufficient size, depth, and fidelity have been unavailable. Here, we present the identification of 164 M7-T9 ultracool dwarfs in 0.6deg^2^ of deep, low-resolution, near-infrared spectroscopic data obtained with the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) instrument as part of the WFC3 Infrared Spectroscopic Parallel Survey and the 3D-HST survey. We describe the methodology by which we isolate ultracool dwarf candidates from over 200000 spectra, and show that selection by machine-learning classification is superior to spectral index-based methods in terms of completeness and contamination. We use the spectra to accurately determine classifications and spectrophotometric distances, the latter reaching to ~2kpc for L dwarfs and ~400pc for T dwarfs.

Cone search capability for table J/ApJ/924/114/ucdwarfs (Late M (Table 3) and L and T (Table 4) dwarfs identified in WISPS and 3D-HST data)

Cone search capability for table J/ApJ/924/114/table11 (*Additional late-type M dwarfs identified in WISPS and 3D-HST data)