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within the PIT CREW and National Center for Rural School Mental Health . Run advanced quantitative analyses using software such as Stata, R, Mplus, HLM, and/or SPSS. Generate research questions
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maintain statistical / machine-learning pipelines (Python / R; Snakemake/Nextflow) for long-read transcriptome assembly, sQTL fine-mapping (SuSiE, Leafcutter) and proteogenomic isoform detection
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commonly used scientific scripting languages (e.g., Python, SQL, or R). We also seek candidates with good communication skills in spoken and written English, and an ability to produce state-of-the art
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ability to learn new software quickly and introduce new useful applications and platforms to the team. Proficient in advanced statistical modeling software (e.g., R, Stata, Matlab) Physical Demands This is
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. Preferred Experience: Experience with GraphPad Prism, R, and/or other statistical software Experience with flow cytometry, western blotting, immunofluorescence, cell culture assays, rodent-based assays, and
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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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(e.g., Python, R, Julia) Excellent written and spoken communication skills A demonstrated ability to produce high-quality, peer-reviewed research Position Details: This position will remain open until
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and fact-finding. Expertise to work on most phases of data analysis and associated programming activities in R or R studio. Analyze and interpret the results of experiments to create cost effective and
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techniques and methodologies. Experience with data analysis software (e.g., MATLAB, Python, R). Excellent organizational, communication, and problem-solving skills. Ability to work independently and as part of
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Familiarity with SPSS, R, or other data management and analysis systems Minimum Requirements: Clinical Research Coordinator 1, Non-Licensed Education: Bachelor's Degree Required or equivalent combination