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move beyond conventional stimuli-responsive materials, which merely switch between predetermined states, toward life-like materials that genuinely learn: Forming memories, consolidating them over time
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characterizing individual nanoclusters • Engineering and purify protein nanopores with tailored sensitivity to size, charge, and etc. • Developing data analysis pipelines and machine learning approaches for signal
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models of regulation and dynamics . Flow- and diffusion-based models of cellular dynamics are expressive enough to map any source to any target state, but they fall short of learning the underlying
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development of metacognitive skills across childhood and adolescence. Metacognitive skills play a central role in successful learning because they enable learners to monitor their own understanding, recognize
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multidisciplinary field, and openness to learning new things. The PhD candidate needs to be proficient in spoken and written English and has a Master’s degree. We are offering a modern research environment and
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environment for doctoral researchers interested in longitudinal and mixed-methods approaches to language learning and mobility.