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Field
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collocates Hawkes (formerly CMIC), UCL’s AI Centre (AIC), and UCL’s Advanced Research Computing Centre (ARC) creating a vibrant hub of data-science researchers with interests from basic machine learning and AI
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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the possibility of extension. For more details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu For questions, please email mweber
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interest in, the political and societal implications of AI and machine learning. Proficiency in English sufficient to discuss research with colleagues and report findings clearly in writing. Motivation
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). Proficiency with programming languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or machine learning applications. Acquisition, processing, and analysis
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Annual Report Individual Appointment Advising Our Programs & Resources Events Upcoming Events Learn about our events Ph.D. Career Stories ASPIRE UP: A Career and Professional Development Series
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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are template based and all US measurements are auto-populated into templates for increased accuracy and efficiency. Fourteen fellowship-trained, subspecialized expert faculty perform both image interpretation
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R