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models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance of design and innovation
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strong command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
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of complex systems, networks, and large-scale data Machine learning, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics
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rapid technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on
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/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related computational fields with expertise in machine learning, natural language processing, human-AI interaction
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in machine learning and formal verification. Individuals with a demonstrated track record in scientific research, which can be evidenced through publications, technical reports, or impactful software
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, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline, organizational behavior, economics, statistics, environmental