It brings together researchers from across disciplines such as chemistry, physics, engineering, data science, and social sciences to develop sustainable materials, processes, and technologies that support a circular economy. This requires an advanced software infrastructure that ties together robotic systems, AI-driven decision-making, experiment orchestration, and scientific data management into a coherent, scalable platform. * Implement and maintain the core software platform for self-driving lab systems, including the service layer, internal APIs, and data flow between subsystems * Implement communication patterns and interfaces between the robotics layer, AI/ML decision engines, and data infrastructure * Apply software engineering best practices: version control, CI/CD pipelines, testing strategies, and documentation standards - Infrastructure & Data Backbone
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