Polymer materials such as thermoplastics, thermosets, elastomers, and gels, were produced on a massive scale of 367 million tons globally in 2020. However, due to their construction at the molecular level, current polymer designs must strike a balance between being hard, durable, and easy to shape or mold. Recent advancements in polymer design take advantage of more flexible molecular connections to open up opportunities for more robust, long-lasting materials. Despite these achievements, making polymers with advanced properties remains a grand challenge because current designs largely depend on the researcher's intuition, and there is limited understanding of how the structure of a polymer determines its properties and how easy it is to process. This collaborative project seeks to use a systematic, data-driven approach to overcome these challenges by developing polymers with adaptive molecular structures that can withstand extreme conditions where they must survive exposure to large mechanical forces and repair themselves when damaged. This research aims to establish a comprehensive, accelerated materials discovery loop that includes multiscale computational simulations, rapid polymer synthesis, automated fabrication with tandem mechanical characterization, and machine learning-guided design. This project aligns with the objectives of the Materials Genome Initiative, using automation, simulations, rapid synthesis, machine learning, and 3D printing to speed up the design and discovery of high-performance polymers. The successful outcome of this collaboration will lead to the creation of polymers with unprecedented mechanical properties and processibility that are suitable for producing wearable sensors, soft actuators, and energy harvesting devices and be compatible with future manufacturing processes.