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scientists. Experience leading with machine learning, predictive modeling, or structure-informed variant analysis. Track record of high-impact publications and active participation in international consortia
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processes (attentional control and working memory) that are known to contribute to language learning, 2) if these cognitive and neural predispositions predict individual rate of subsequent language learning
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and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. In the Division of Chemical Biology , we combine and develop protein engineering, synthetic
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the solar system either, is challenging our standard models of planet formation. Our goal is to predict and reproduce the architecture of these exoplanetary systems and the exoplanet properties, including
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prototyping, fabrication experiments, development of experimental setups, material testing, design modelling and optimisation, and the preparation of workflows interfacing with robotic and construction
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of the formal document. For additional information on this matter candidates are advised to check the website of the Directorate-General for Higher Education (DGES): https://www.dges.gov.pt/en/pagina/degree-and
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– and building on recent advances in foundation models, neural model predictive control, and robotic world models – this PhD project will investigate principles and mechanisms for a shared autonomy
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support, data migration, and integration projects. Assists with pilot data science and predictive analytics projects as needed. Participates in the development of Business Intelligence (BI) and other
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machine learning pipelines, with GPU-accelerated environments tailored to foundation model training, data harmonization, and predictive analytics. The Center is embedded within the UC Davis ecosystem, with
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alters feather identity; and (3) mathematical modelling of the GRN to predict the regulatory logic required to stabilise flight feather formation and simulate possible evolutionary scenarios