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at the intersection of AI and any humanities or social science discipline. Fellows will have the option to teach one undergraduate course each year. The first year of appointment will run 1 August 2027–31 July 2028
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world and a suite of associated machine learning tools. The incumbent will be advised by Dr. Laurel Symes (CAPS, [email protected]). Depending on the research direction, collaboration and additional
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avenues of research rather than a required work plan. They may be pursued individually or in combination, and we welcome other creative and strategic approaches. Statistical or machine-learning approaches
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. Applications are welcome from scholars in relevant fields in the humanities and social sciences. The successful candidate will pursue an independent research agenda; teach one undergraduate course in each year
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to): biophysics, cold atom physics, electronic structure theory, hydrodynamics, machine learning, materials science, statistical physics, strongly correlated electrons, and quantum information. Theorists who wish
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across learning sciences, computer science, machine learning, HCI and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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, hydrodynamics, machine learning, materials science, statistical physics, strongly correlated electrons, and quantum information. Theorists who wish to be considered for sponsorship as a Klarman Fellowship
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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including historical linguistics, semantics, pragmatics, computational linguistics, phonology, or sociolinguistics. We would like to see candidates who can communicate with and learn from both linguists and
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activity consistent with a Research I university. Postdoctoral Fellows teach one course per semester, including one lower, 2000-level course and one upper, 4000-level course each year. Candidates should