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Computer Engineering. Expertise in computer vision algorithms and image processing techniques (such as object detection, segmentation, and feature extraction). Proficiency in deep learning frameworks such as
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, deep tech, and venture capital. The ideal candidate is a proactive, service-oriented communicator who enjoys collaborating with others to iteratively refine products to perfection. Workplace Requirements
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Specialized areas: Deep Learning, Generative AI, Prompt Engineering, Conversational AI and Chatbots, Reinforcement Learning Applied domains: Machine Learning for Cybersecurity, AI for 3D Imaging, Recommender
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and executive levels, all of them enriched by the dynamism and deep resources of one of the world's business capitals. NYU Stern is a welcoming community that inspires its members to embrace and lead
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portfolio of transformational programs at the graduate, undergraduate and executive levels, all of them enriched by the dynamism and deep resources of one of the world's business capitals. NYU Stern is a
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at the intersection of mathematics and AI safety, with a focus on developing rigorous mathematical foundations for AI interpretability. Research directions include mean field theories of deep learning, data attribution
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense
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methods (e.g., deep learning, generative models, representation learning) ● Experience working with large public biological datasets/repositories (e.g., GEO, SRA, UK Biobank, GTEx, etc
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assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment