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to preventive interventions, decision support to implement mental health interventions, longitudinal data analysis, machine learning/NLP/AI, integrative data analysis, and related grant writing. This candidate
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recruitment and buy-in, CARE program implementation and fidelity of implementation monitoring, and data analysis and manuscript generation. This position will complete duties as follows: Recruiting: Reaching
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of them are required at start date. Cell culture: Culture of various cell types (cancer cells, stem cells, primary cells, organoids, neurospheres). Cell cycle analysis, 2D/3D colony formation assays, siRNA
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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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, if desired. This position is located in Charlottesville and is planned to start on or around July 1, 2025. Role and Responsibilities- The CASTL Post Doctoral Research Associate will help with data analysis and
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well as testing effectiveness of implementation supports (e.g., professional learning communities and coaching). Responsibilities: Coordinating data collection and analysis activities. Developing and disseminating
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for data analysis and research. Machine Learning Skills: Experience with machine learning algorithms, transformers, or large language models to analyze genomic data. Computational Proficiency: Skilled in R
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publications, conference presentations, and policy white papers Develop and implement data analysis pipelines for large-scale datasets Present research findings at conferences and professional meetings
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pathways by HSV-1 UL12.5 for reactivation from latent infection. Krakowiak PA et al Proc Natl Acad Sci U S A. 2025 Jan 28;122(4):e2413965122.doi: 10.1073/pnas.2413965122 . Single-genome analysis reveals a
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scientist with a strong background in single-cell genomic data biology and analysis to contribute to this important work. The successful candidate will work on uncovering pathways that drive susceptibility