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the study of plant-plant or plant-invertebrate interactions Experience in nematology or nematological methods Strong quantitative skills (e.g., generalized linear mixed models, permutational methods, Bayesian
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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins), Participants will collaborate closely with other Doctoral Candidates and
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levels. Contributing to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins), Participants will collaborate closely
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surveys, interviews, and workshops. Produce publishable contributions at the intersection of AI, Human-Computer Interaction, and Digital Health, with targeted venues including AAAI, ACL, NeurIPS, ICML, ACM
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and quality issues in real-time. Supporting Digital Twins: Play a crucial role in developing the next generation of computer platforms that support the prevention, diagnosis, and management of endocrine
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research with ~40 patients living with adrenal insufficiency using surveys, interviews, and workshops. Produce publishable contributions at the intersection of AI, Human-Computer Interaction, and Digital
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to automatically identify, flag, and mitigate data artifacts and quality issues in real-time. Supporting Digital Twins: Play a crucial role in developing the next generation of computer platforms that support the
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classification Estimation of the probability of developing diseases Anomaly detection Early diagnosis. The recipient will learn and apply a vast portfolio of complementary and synergic methods at the intersection
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-physiology models of interest for: Phenotype classification Estimation of the probability of developing diseases Anomaly detection Early diagnosis. The recipient will learn and apply a vast portfolio of