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system. For the meta-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine
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. The successful candidate will join the Ryan Lab which is based in the Division of Earth and Climate Sciences in the Nicholas School of the Environment at Duke University. The Ryan Lab studies interactions between
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pathways and mechanisms underlying autoimmunity from a lncRNA and epigenetic gene regulation perspective. We utilize biochemical assays, tissue culture, mouse transplantation & disease modeling experiments
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computational and data analytical methodology development and implementation; experience in supervised and unsupervised machine learning, low-dimensional models or deep learning models, and willingness to learn
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-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine learning is desired
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with various methods that can incorporate domain-based constraints and other types of domain knowledge into machine learning and applying these techniques to problems in computational creativity
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postdoctoral trainee and fellows stipend levels based on the candidate’s experience. The start date will be during the Summer 2025. Review of applications will begin immediately and will continue until
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models using a wide variety of data, including clinical, wearable devices, neuroimaging, and –omics data from electronic health record, registry, and research initiatives; and (2) develop and apply novel
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on innovative projects exploring receptor-specific contributions to behavior and circuit function. Work Performed • Conduct stereotaxic surgeries and pharmacological manipulations in mouse models. • Perform
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, work will involve the evaluation and modeling of plastic fragmentation and additive release from plastics as well as life cycle assessment of materials processing. Candidates should have a doctoral