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, and mathematical data science, with an active programme at the interface of dynamical systems, machine learning, and quantum information. The position sits in the GOAL group (GeOmetry, dynAmics, and
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sensing systems (wearable, ambient, RF, distributed), edge and on-device data processing and machine learning, resilient distributed architectures for sensing, sensor-data fusion and analytics
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PhD candidate will have: A strong background in computer science, artificial intelligence, machine learning, or a closely related field. A solid understanding of machine learning concepts, particularly
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of optimization and generalization to inform the design of practical training algorithms. To produce high-quality publications in top-tier machine learning conferences and journals. To offer guidance and assistance
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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to [email protected] For more information about working at
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Cornell Tech, the Associate Director of Technical Programs and Student Life is responsible for overseeing key operational aspects and serving as the primary contact for Cornell Tech PhD, and technical
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, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage
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theories in inverse/scattering problems. Once successful, the candidate is expected to transfer his expertise to machine learning/scientific computing in collaborations with other group members (phd students
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research