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of national research infrastructures. The ideal candidates will have a PhD in a discipline closely related to computational social science by date of appointment (e.g. network science, computer science, data
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disease (CAD). You will apply expertise in data science, machine learning, as well as multi-omics integration to predict and validate functional regulatory networks in vascular cell types. This work will
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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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Center. The broad areas of interest in Dr. Trinh's lab include: gene regulation by RNAs and proteins, modulation of gene-specific chromatin architecture, blood development, cancer and genetic diseases
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. This position offers a unique opportunity to contribute to high-impact, interdisciplinary research at the intersection of network science, global research competitiveness, and generative AI capabilities
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within broader gene networks regulating islet autoimmunity. This project involves generating data from longitudinally collected human peripheral blood mononuclear cells at the single-cell level (CITE-seq
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content creation (e.g., research briefs to research and school partners), technical assistance, and presentations. Knowledge/Skills/Abilities: Content expertise in some of the following areas: mental health
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area of particular interest in the lab is glioblastoma. Glioblastoma is the most frequent and most aggressive cancer type of the brain which to date is still considered a deadly disease. A significant
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, school social work, public health, educational policy or related discipline is required by the start date of the position. Supporting school mental health services, especially in high-need schools
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their communications Data Collection and Analysis: Collect data on the implementation process, including facilitator performance and participant feedback Analyze fidelity data to identify areas where