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Field
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at Northeastern. (10%) Required Qualifications: - Ph.D. in Human-Computer Interaction, Information Science, Computer Science, Design, or related fields - Strong record of published research in HCI, CSCW, DIS
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use of molecular assays such as real-time PCR and next-generation sequencing to study the prevalence of infectious diseases in the target study populations. Learning about sample testing under a
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Associate/Research Fellow with expertise in Artificial Intelligence (AI)/Machine Learning (ML), pedagogical research in Institutes of Higher Learning (IHLs), and web/mobile application development (both
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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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(CBmE) was established in September 2006 in the Yong Loo Lin School of Medicine through a generous gift by the Chen Su Lan Trust. CBmE, directed by Prof Julian Savulescu, is a thriving centre for learning
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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stimulating community. Fellows teach one small seminar during their fellowship year appropriate for graduate students and advanced undergraduates. Though courses are designed to fit the focal theme
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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methods to economic and environmental problems; Knowledge of STATA, R, Python and/or other relevant programming skills for undertaking applied analysis (e.g. machine learning) and handling large
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year postdoctoral position. Using recent