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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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design: difference-in-differences and fixed effects models, instrumental variables, treatment selection, power analysis, analysis of attrition and non-compliance, analysis of heterogenous effects and
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Staff Services office. Candidates should have some familiarity with some or all of the following: · Causal analysis and experimental design: difference-in-differences and fixed effects models
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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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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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the feasibility, scalability, and effectiveness of different approaches to the skills challenge. An ideal candidate will be interested in conducting cutting edge research on reskilling initiatives both
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employees, whose jobs are being replaced by digital technologies. The Lab partners with organizations to test the feasibility, scalability, and effectiveness of different approaches to the skills challenge
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, processes, material objects, and built environments through which a group endeavors to remember, and often honor, people, happenings, or values of the past. We will seek participants working at different
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is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston