Scientific Analyst I - Department of Pediatrics

The Department of Pediatrics, PANDA Core for Genomics and Microbiome Research at the Steele Children's Research Center, is recruiting a Scientific Analyst I to provide computational analysis and bioinformatics support for genomics and microbiome research projects across the University of Arizona Health Sciences. The incumbent gathers and analyzes data from sequencing platforms and public databases, performs statistical and mathematical programming in R and Python in a Linux environment, and develops reports, visual representations, and draft results for principal investigator review. The incumbent collaborates directly with investigators in designing studies, selecting appropriate analytical methods, and preparing data and figures for publication. The incumbent also develops and maintains analysis pipelines and project databases, evaluates new platforms, techniques, and scientific programs, and provides consultation and technical assistance to Core clients.

Visa sponsorship is not available for this positions.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!
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• Gather and analyze data from various databases and sources; perform statistical and/or mathematical programming; develop reports and visual representations.
• Process raw sequencing data through established Core pipelines, including 16S rRNA amplicon (DADA2), shotgun metagenomic, and bulk RNA sequencing analyses.
• Perform routine computerized data reduction and analyses, including statistical computations, differential abundance testing, and differential expression testing.
• Generate draft statistical reports, summary tables, and publication-quality figures, and perform an initial interpretation of results for PI review.
• Prepare draft research progress reports summarizing analytical results for PI review.
• Develop and/or maintain databases, and provide consultation, technical assistance, and coordination for a wide variety of investigators or other research faculty.
• Maintain project databases, sample metadata records, and analysis directories on Core and high-performance computing storage.
• Maintain and document reproducible analysis workflows and scripts in R, Python, and shell under version control.
• Track project status and deliverables across concurrent Core projects and coordinate delivery of results to investigators.
• Assist investigators in determining the appropriate statistical methodology to meet their study needs and objectives.
• Participate in project intake meetings with investigators to document study objectives, analysis plans, and deliverables
• Assist investigators with experimental design questions, including sample size, sequencing depth, and control selection, based on established Core standards prior to sample submission.
• Use statistical and mathematical software packages to summarize and interpret statistical results.
• Coordinate study analysis activities for assigned projects.
• Support dissemination of research results and evaluate new platforms, techniques, and scientific programs.
• Assist investigators in the preparation and writing of methods, results, figures, and legends for manuscripts and grant proposals.
• Research and evaluate new software and analytical methods for potential use by the Core.
• Produce written summaries of method benchmarking and comparisons for Core leadership.
• Present analytical results and method updates to internal team members and Core clients.

Knowledge, Skills, and Abilitie:

• Knowledge of general principles, theories, and concepts of genomics and microbiome research, and of industry practices, techniques, and standards.
• Knowledge of next-generation sequencing data types, including 16S rRNA amplicon, shotgun metagenomic, and RNA sequencing data.
• Skill in scripting and statistical programming in R and Python.
• Skill in working in a Linux command-line environment, including the use of high-performance computing resources.
• Skill in microbiome sequence analysis using established pipelines such as DADA2 and QIIME 2.
• Skill in RNA-seq analysis, including alignment, quantification, and differential expression testing.
• Skill in applying biostatistical tools used in the biological sciences and in database development and management.
• Skill in producing effective written communication, including reports, figures, and manuscript-ready materials with limited supervision.
• Ability to explain technical methods and results clearly to investigators without a computational background.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

• Bachelor's degree in bioinformatics, computational biology, biostatistics, microbiology, molecular biology, or a closely related field, or equivalent advanced learning attained through experience, required.
• Up to one (1) year of relevant work experience required.

• Master's degree in biological sciences or a closely related field.
• Experience analyzing microbiome sequencing data (16S rRNA amplicon and/or shotgun metagenomics).
• Experience with RNA sequencing analysis workflows, from raw reads through differential expression.
• Experience with version control (Git) and reproducible workflow managers such as Snakemake or Nextflow.
• Experience supporting multiple investigators in a core facility or other service-oriented research environment.
• Experience preparing figures, methods sections, and data submissions for peer-reviewed publications.
• Familiarity with public sequence repositories (SRA, ENA, GEO) and their data submission requirements.

Application: The online application should be completed in its entirety. Blank or missed information may be considered an incomplete submission.

Cover Letter: Should clearly indicate how your skills and professional employment experience meet the Minimum and the Preferred qualifications (if applicable).