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-polymers using AI-driven process intensification, safe-and-sustainable-by-design principles, and smart polymer formulation. The project brings together leading academic and industrial partners to create a
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the monomers are reversible, making these polymer materials adaptive, healable, easy to process and recyclable. In this project, you will explore new types of stimuli-responsive supramolecular polymers
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include developing efficient code in Python and Julia to perform numerical optimization of control fields that govern the evolution of the photonic quantum information processor. This includes adaptation
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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models