13 molecular-modeling-or-molecular-dynamic-simulation research jobs at University of Virginia
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The laboratory of Dr. MariCarmen Lafita-Navarro in the Department of Biochemistry and Molecular Genetics at the University of Virginia (UVA) School of Medicine is seeking to fill an exciting
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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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normal and cancer cells, and mouse models. Research in the Trinh lab centers on protein- and RNA- mediated gene regulation via modulating chromatin architecture in development of immune cells, particularly
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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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to type 1 diabetes (T1D). The Onengut Lab integrates genetics, molecular biology, and bioinformatics to investigate how genomic loci linked to T1D contribute to disease mechanisms at the molecular level and
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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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Join our dynamic team at OCIR, where we specialize in orthopedic surgical care, with a focus on same-day joint replacement procedures. We offer a comprehensive 23-hour overnight stay for patients
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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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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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for Nurses with Interpretive Statements, and the UVA Nursing Professional Practice Model. Relationship Based Care - Self and Colleagues: reflects the influence of the nurse’s relationship with self, colleagues