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longitudinal studies. Particular analyses will adapt techniques from psychometrics, including item response theory and factor analysis, to analyze the LEVANTE data. These analyses will include examination of how
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Biology, Bioinformatics, Computer Science, or a related field • Strong programming skills in R and/or Python • Experience with analysis of single-cell sequencing data • Familiarity with spatial
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most significant genetic risk factor. Individuals carrying one copy of APOE4 have approximately a 4-fold increased risk of developing AD, while those with two copies face a 15-fold increased risk
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or involved in RAPID surveys. This project constitutes a critical component of the New Ecology of Early Childhood (link is external) being developed at SCEC. Key Responsibilities: Conduct statistical analyses
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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psychology) or related discipline. Demonstrated interest in measurement of psychological constructs and study of change. Substantial experience with latent variable models (especially factor analysis, item
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
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, Tumor Immunology, Molecular Biology, Protein Biology, Mouse work, Flow Cytometry/FACS, LC-MS/MS, TCR- and RNA-seq, and AI analysis. Required Application Materials: CV, research summary, and published
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meetings Key Responsibilities: Development and implementation of study protocols Participant recruitment and collection of participant and laboratory data Statistical analysis of data Authorship
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research activities, the fellowship emphasizes capacity-building in grant writing, manuscript preparation, advanced data analysis techniques, and the art of mentoring and supervising burgeoning scholars. We