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reproducible methods to complex population, clinical, and molecular data using R, Python, SAS, or related tools, with well-documented code and analytic workflows. Collaborate and communicate effectively with
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CRISPRi/a screening (Cell Stem Cell 2024), 3) Deciphering pathogenic coding and non-coding variants linked to congenital heart disease in a cell type-specific manner (Cell 2022), and 4) Combining iPSC
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Contribute to data presentation to collaborators and in meetings and conferences The ideal candidate will additionally have experience in: Duplex sequencing analysis Statistical analysis Advance coding in R
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of interest describing their relevant skills, experience and interests (maximum of 2 pages) Curriculum-vitae including a list of publications and links to any open code repositories Names and contact
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, Geology, Earth Sciences, Civil and Environmental Engineering, Coastal Engineering, or related fields. The successful candidate will have a strong background in numerical modeling and coding (Matlab
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for funders, public research briefs and literature reviews, public coding syntax files, and peer-reviewed journal articles. There are possibilities for travel and fieldwork in focus geographies as needed. Some
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interest describing their relevant skills, experience and interests (maximum of 2 pages) (2) a curriculum-vitae including a list of publications and links to any open code repositories, (3) the names and
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the group members. Write computer codes for the above data modalities under the guidance of the team leader. Engage in the development and testing/validation of new quantitative AI algorithms and their
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Cell 2024), 3) Deciphering pathogenic coding and non-coding variants linked to congenital heart disease in a cell type-specific manner (Cell 2022), and 4) Combining iPSC-derived cells and single-cell
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, including time series analysis Record of mentoring or developing junior employees on soft and technical skills Advanced experience developing code in Python and R, and familiarity modeling with multi