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-edge research at the interface of operations research, optimization, and machine learning, with a focus on quantum optimization . Background in discrete and non-linear optimization is preferred. The term
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observational data of non-CO 2 greenhouse and ozone-depleting gases (e.g., N 2 O, CFCs, HFCs), and to extract diagnostic insights from instrument performance indicators, using machine learning methods
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observational data of non-CO 2 greenhouse and ozone-depleting gases (e.g., N 2 O, CFCs, HFCs), and to extract diagnostic insights from instrument performance indicators, using machine learning methods
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digital transformation, machine learning, and data analysis applied in logistics and supply chain management; support graduate-level teaching activities for both the Supply Chain Management residential
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transformation, machine learning, and data analysis applied in logistics and supply chain management; support graduate-level teaching activities for both the Supply Chain Management residential (SCMr
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for specific student segments (child vs. adult learners) Publish high-quality research results in top-tier venues spanning machine learning, reinforcement learning, embodied AI, and AI in education
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machine learning, such as reinforcement learning, deep learning, generative AI, multimodal AI, statistical modeling, and network analysis. Preferred experience in the following areas: Recommendation
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: Experience with general methods in artificial intelligence and machine learning, including reinforcement learning, deep learning, generative AI, multimodal AI, and LLM. Experience in the integration of
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Appointment Duration: 1-year appointment with possibility of renewal for a 2nd year. About the Department Our research group works at the intersection of machine learning, medical imaging, biomedical
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mathematical background, excellent programming skills, and proficiency in machine learning frameworks such as Python, C/C++, TensorFlow, and PyTorch. 4. Hands-on experience with ultrasound systems