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Field
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the dissertation, must be completed by the date of appointment. Demonstrated research experience with density functional theory or closely related first-principles atomistic simulation methods. Demonstrated research
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with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction or a related field who enjoy making empirical, methodological, and technical contributions
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of recent theories related to charge ordering. • Design and implementation of experiments on thin-film growth and topotactic reduction; • Active participation in synchrotron measurement campaigns in France
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and technical papers for publishing. Investigates the feasibility of applying a wide variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and
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for an additional year) in quantum condensed matter theory. Candidates with research interests in any of the following areas of quantum condensed matter theory will be preferred: nonequilibrium physics, strongly
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connecting governance studies at all levels of global society. Qualifications The ideal candidate will have completed a PhD in intellectual history, history, political sociology, political theory or political
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demographic research has developed numerous theories of fertility and produced a sophisticated body of work on the many characteristics associated with fertility. Despite this, we are poorly able to predict
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swimming. The successful candidate will lead quantitative analysis of animal configuration and related flow field topology utilizing graph theory to assess the impact of swimming and environmental conditions
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to think independently, in human-AI interaction. You will connect the project's technical work with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction
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to characterize the brain network interactions using connectivity and graph theory metrics. Develop reproducible computational pipelines in MATLAB, Python, R, or similar platforms for electrophysiology processing