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Field
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Responsibilities: · Develop novel statistical methods for robust pathway analsysis · Develop novel statistical methods for spatial transcriptomics data analysis · Data management · R
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Biostatistics, Statistics, Epidemiology, or a relevant Public Health field. Strong background in statistical modeling, inference, and data analysis. Proficiency in statistical analysis software such as Stata, R
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and helping to recruit and retain clinically diagnosed samples for research studies. Strong applicants will also have experience conducting statistical analyses and creating data visualizations in R. A
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(Perl or Python, R, Linux tools, bash scripting) Experience in presenting at conferences Excellent publication record Strong motivation and dedication, scientific writing skills, problem-solving skills
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, or corporate stakeholders. Must possess strong interpersonal skills to co-create knowledge and initiatives across disciplines and roles. Desired: Experience with R coding; strong verbal and written communication
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, or similar platforms for thermal and fluid dynamics simulations. Strong programming skills in MATLAB, Python, R, or similar. Machine learning or data-driven modeling experience applied to environmental control
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scheduled to run in CY26 Lead role in our MCP-PMT R&D program, with emphasis on device characterization and QA You may combine these focus areas with other ongoing projects in our group. About Argonne and the
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, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family
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: C++, Python, Matlab, R. ● Building analytical pipelines that include image processing, image registration, auto-segmentation, feature extraction, pathomics, and radiomic analysis ● Proficiency
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epidemiologic and biostatistical training and be proficient with R-statistical software. Prior experience with single omics data and multi-omics integration (e.g., DNA methylation, transcriptomics, proteomics