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/or experience with large-scale data analysis, algorithm development, or computational modeling. Required Qualifications: Doctoral degree in linguistics, cognitive science, psychology, hearing and
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experience with latent variable models (especially factor analysis, item response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex
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, econometrics/causal inference, data management, coding (e.g., in Stata or R), and applied policy-relevant research. Skills in geospatial analysis and/or data visualization would be a plus. The candidate should
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, single cell and multi-omics data analysis, and a high-performance computing environment (Unix/Linux) is highly preferred. An individual with Next generation sequencing experience is preferred. A good
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biology, cancer biology, and/or molecular biology preferred • Experience in image processing and analysis also preferred • The candidate will report directly to the Principal Investigator and will
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Strong quantitative and analytical skills Experience in either experimental neuroscience (e.g., in vivo neurophysiological recordings, behavioral training) or computational data analysis (e.g., spike
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isolation, library preparation, and analysis and interpretation of genomic data. A deep understanding of bulk and single-cell sequencing assays is highly desirable. Familiarity with brain development, brain
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. The current project uses structural neuroimaging to guide DBS lead placement and optimal DBS settings, as well as kinematic analysis of behavioral motor tasks. Additional projects include the development of a
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will bridge data, operations, and policy to integrate forest-management realities with the use of biochar technology as a wildfire mitigant and ultimately provide analysis to its economic feasibility
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attend seminars and speaker series and will be able to audit courses offered by the GSE to strengthen or expand their analytic skills (via courses offered by the Center for Education Policy Analysis and