Computing systems in space enable essential technologies like GPS, satellite communications, and agricultural monitoring. However, these systems face harsh challenges, particularly radiation, which can severely degrade or destroy electronic components. Traditional radiation-hardened techniques that address this challenge are both costly and based on outdated technology, limiting performance and flexibility. At the same time, renewed interest in lunar and Martian exploration is driving demand for far more capable space-based computing. Fortunately, a promising approach called in-memory processing is being explored where memory directly performs computation. Using this method, memory can function like an accelerator suitable for enabling state-of-the-art image and signal processing and artificial intelligence (AI) approaches that would be otherwise impractical. Memory-based acceleration reduces the burden on and complements central processors for space computing systems. The RADIANT project investigates whether modern commercial memory devices, not originally designed for space, can function reliably and provide in-memory processing capabilities in radiation-rich environments through appropriately-designed error correction techniques. The research supports national priorities by advancing space computing capabilities, while also offering interdisciplinary education opportunities that span computer science, engineering, and physics. RADIANT has two main technical goals. Firs