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that integrate population genetics, statistical analysis, and health data. You will directly contribute to deeper analysis of data derived from the HGSC's pioneering work in Mendelian genomics and multiple NIH
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the Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, has 3 postdoctoral researcher positions available in statistical genetics and generative AI models. Statistical Genetics postdoc
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of statistical research will be given full consideration. We are particularly interested in candidates with collaborative research interests in study design and analyses of therapeutic and non-therapeutic
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, databases, text). Conducts statistical analyses and visualize results. Extracts meaningful insights from complex data. Develops predictive models using supervised and unsupervised learning approaches
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statistical and qualitative analyses on new and available data sets. Collates evaluation data and other quantitative and qualitative data sources. Prepares comprehensive documented observations, analyses and
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. Experience in the analysis of single cell RNA-sequencing and spatial transcriptomics data is advantageous, and proficiency in statistical analysis tools such as R or Python is desirable. Interested candidates
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, or full Professor) with a Ph.D. and/or M.D. in Computational Biology, Bioinformatics, Genetics, Genomics, Statistics, or a related field for the following two positions: Molecular Epidemiologist: Candidates
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strong background in programming or statistics together with a familiarity with bioinformatics tools. No wet lab or laboratory experience is desired or required. All projects are jointly supervised by
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. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Experience in epigenetics or gene regulation is a plus, and experience with statistical analysis
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., DNA-seq, RNA-seq, metabolomics, proteomics). • Preference will be given to candidates with experience in integration of multi-omics data. • Programming experience in statistical program R and/or