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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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. • Possess molecular virology or protein biology skills. • Should be enthusiastic and dedicated, have the ability and interest in learning new techniques; must be able to follow verbal and written instructions
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with experts in AI and machine learning. The post-doctoral associate will also be responsible for data management and dissemination of scientific results. The successful candidate will join a
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in areas related to quantum information theory, quantum error correction, and machine learning. The position will start in fall 2026 and will be for two years, with a possible 1-year extension pending
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. Responsibilities: • Design and conduct experimental research on paper-based materials for food packaging applications. • Develop predictive models for packaging performance using machine learning and physicochemical