The Intelligent and Interactive Systems lab uses machine learning to enhance the flexibility, robustness, generalization and explainability of robots and vision systems, focusing on methods for learning about structure, function, and other concepts that describe the world in actionable ways. Three University-Assistant Positions involve minor teaching duties with negotiable research topics within the lab's scope. One Project Position involves the integration of robotic perception and execution mechanisms for task-oriented object manipulation in everyday environments, with a focus on affordance-driven object part segmentation and object manipulation using reinforcement learning.