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Field
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surveys, laboratory experiments, and advanced analytical tools. Water and plankton samples from UK coastal waters will be analysed to quantify MNP types, sizes, and concentrations, correlated with plankton
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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forces behind the ageing audience by developing an age-period-cohort perspective. The project harmonizes survey data collected over long time periods, collects new survey data about attendance, and
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groups, participatory action methods. Partner with and support the Senior Research Associate on the National Purpose Survey, the first nationally representative longitudinal sample investigating diverse
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the following requirements: The PhD must have been granted at less than two years; Proven experience in vegetation studies and floristic surveys - information provided in the CV and/or in the motivation letter
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for conference travel, and for data collection (e.g. survey, or survey experiment/s) for their PhD project. Candidates should have a Master degree (with Distinction, or Merit with a Distinction in the dissertation
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affective attitudes toward aging are assessed in a sample of N = 150 parent-child dyads – both implicitly and explicitly. Modern methods of attitude research, observation procedures, and child-friendly
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investigate how misinformation can reinforce existing beliefs, and emphasize the role of group dynamics and communicative features therein. In multiple surveys and experimental studies, we determine whether, to
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communicative features therein. In multiple surveys and experimental studies, we determine whether, to what extent and how misinformation impacts these at-risk individuals. Subsequently, we develop and test new
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, indicators and survey information. The division combines structural macroeconometric modelling with data-science methods for nowcasting, high-frequency indicators construction, machine learning, time-series