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cardiovascular treatments. In this role you will apply both machine learning predictive modelling and human genetic analyses of non-coding regulatory sequences to identify cell-specific targets for coronary artery
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disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response
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The lab of Professor Alexander Gates, the Connected Data Hub, together with the School of Data Science at the University of Virginia, is looking for a Postdoctoral Research Associate in the area of
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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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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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of national research infrastructures Evaluating the evolution of Generative AI performance over time and across tasks Analyzing international AI models and their representations of the U.S. in global discourse
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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molecular mechanisms of carcinogenesis from a developmental perspective using Neurofibromatosis Type 1 (NF1), a common tumor predisposition human genetic disorder, as a model. While working on
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research using complex observational healthcare data, with a focus on cancer studies. The successful candidate will be expected to: Modeling multilevel survival data while addressing confounding and missing
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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