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§ Clinical metadata harmonization across cohorts § Integration of clinical and multi-omic microbiome data. § Experience with Python/R and cloud computing preferred Ideal candidate: A computational
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., public health, psychology, aging, health communication) from an accredited university. Experienced in statistical packages (e.g., R, SAS, SPSS, Stata). Eligibility for RN licensure in the state of Arizona
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Qualifications: Experience with analyzing data in R. Experience studying biotic interactions as preserved in the fossil record. Experience with identifying late Cenozoic molluscs. Experience with assembling a
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. Strong programming and analytical skills (e.g., Python, R, GIS, modeling frameworks). Experience working with EO data, disease surveillance data, or socio-environmental modeling. Demonstrated interest in
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-on proficiency in using pharmacometrics tools including but not limited to NONMEM, R and Phoenix. Understanding of pharmacometric principles and incorporation of M&S strategies. Ability to develop and deliver
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visualization in R and/or Python. Ability to work closely with experimentalists to ensure analyses complement experimental goals and enhance data interpretation. Advanced Computational Skills: Proficiency in
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, quantitative psychology or a related field at the time of appointment. Experience working with complex survey data. Highly proficient in R, SAS, and/or STATA. Demonstrated ability to work in a highly
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designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical
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skills (e.g., Prism, Python/R, HTS analytics) and clear scientific writing/presentation ability · Genuine enthusiasm for mentoring and cross-disciplinary teamwork City of Hope employees pay is
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that applicants follow the Fellowship (F) instructions in the SF424 (R&R) Application Guide except where instructed to do otherwise (in this FOA or in a Notice from the NIH Guide for Grants and Contracts