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more complete picture of how processing speed is related to health outcomes. The candidate will work in a multidisciplinary environment consisting of PhD-level scientists, graduate students and
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multiphysical loading regimes including hydraulic, thermal, and chemical processes. The direct applications of these research will be aimed at enhanced modeling of hydraulic fracturing and carbon sequestration
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the prospective postdoc candidate. The post-doctoral associate will spend half their time on independent research, and half their time on collaborative research with Professors Alaïs Martin-Baillon, Jordan Norris
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ecosystems. We seek an outstanding researcher who already has a demonstrated record of publishing rigorous work in leading AI, NLP, Web, computational-social-science, human-computer-interaction, or
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before starting—in computer science, electrical or computer engineering, information science, or a closely related discipline. Less than 5 years post receiving the Doctoral degree. Meet the mandatory
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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and biophysics, good computer programming skills, and working knowledge of UNIX, phyton, and shell scripting is highly desired. Experience in molecular simulation softwares and analysis tools such as
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distributed decision-making. Applicants must have a PhD in Electrical Engineering, Mechanical Engineering, Computer Engineering, Applied Mathematics, Mathematics, or a closely related discipline, and are within
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mission is research and education in artificial intelligence, specifically focusing on natural language processing, computational linguistics, and data science. The main lab research areas are Arabic
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on natural language processing, computational linguistics, and data science. The main lab research areas are Arabic natural language processing (orthography normalization, grammatical error correction