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and in vitro model systems to test novel biological mechanisms. Techniques of interest focus around high-dimensional immunophenotyping via mass cytometry and spectral flow cytometry, immunofluorescence
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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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cell biology. Additional preferred qualifications include: experience in mouse models of disease, flow cytometry, single-cell RNA sequencing analysis, and image processing and analysis. Qualified
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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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science of science, network science, and natural language processing. As part of a small research team, the postdoc will help lead efforts to provide a quantitative model of global competitiveness
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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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ability to learn new software quickly and introduce new useful applications and platforms to the team. Proficient in advanced statistical modeling software (e.g., R, Stata, Matlab) Physical Demands This is
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on the potential survival of consciousness after death. Today, our broad mission is the scientific investigation of phenomena that challenge currently accepted models of the nature of mind and consciousness
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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