Research Aide

Arizona State University • Tempe, AZ

1d • Onsite

About The Position

The Research Aide in the Center for Environmental Health Engineering provides routine, technical, and administrative support to research projects to ensure established protocols and procedures are followed for the lab, and is responsible for following lab safety standards. This role will support interdisciplinary research focused on understanding and modeling human exposure to pathogens in environmental systems. It involves compiling, cleaning, and analyzing complex environmental and epidemiological datasets, and contributing to the development of computational and probabilistic models. The aide will gain hands-on experience in data-driven research, quantitative risk assessment, and environmental health modeling, with a particular focus on antimicrobial resistance (AMR) transmission pathways across environmental media such as water, soil, and air. This is a temporary position for the Summer 2026 with an anticipated start date of May 25, 2026 through August 16, 2026, and provides an opportunity to collaborate with researchers across engineering, microbiology, and public health disciplines, and to contribute to high-impact research outputs, including technical reports, peer-reviewed publications, and presentations.

Requirements

• High School Diploma
• Any equivalent combination of experience and/or training from which comparable knowledge, skills and abilities have been achieved.

Nice To Haves

• Enrolled in or recently completed a bachelor’s or graduate degree in Environmental Engineering, Public Health, Microbiology, Data Science, Statistics, or a related field.
• Basic proficiency in R, Python, other coding software tools, or other statistical/computational software.
• Foundational knowledge of statistical analysis and data interpretation.
• Experience writing and conducting literature reviews and summarizing scientific findings.
• Strong written and verbal communication skills, with the ability to present technical information clearly.
• Ability to manage multiple tasks, meet deadlines, and work both independently and collaboratively.
• Experience with probabilistic modeling, quantitative microbial risk assessment (QMRA), or environmental exposure modeling.
• Demonstrated experience using R for statistical analysis, including packages for simulation and data visualization.
• Familiarity with Monte Carlo simulation, sensitivity analysis, and uncertainty quantification techniques.
• Experience conducting systematic reviews using PRISMA or similar frameworks.
• Prior involvement in preparing or contributing to peer-reviewed journal publications.
• Experience working with environmental or epidemiological datasets.
• Knowledge of antimicrobial resistance (AMR), microbial ecology, or environmental health systems.
• Strong attention to detail, particularly in data extraction, coding, and documentation for reproducibility.

Responsibilities

• Assist senior staff in the preparation and implementation of probabilistic and stochastic models to assess antimicrobial-resistant bacteria transmission in environmental systems.
• Compile, clean, and manage large datasets from multiple sources (e.g., published literature, environmental monitoring data, public databases).
• Conduct systematic literature reviews using established methodologies (e.g., PRISMA), including screening, data extraction, and documentation of inclusion/exclusion criteria.
• Extract quantitative data from peer-reviewed studies to support modeling efforts, including parameter estimation and uncertainty analysis.
• Support the preparation of reports, manuscripts for peer-reviewed journals, and presentations.
• Collaborate with interdisciplinary team members to interpret results and translate findings into actionable insights.
• Maintain organized documentation of datasets, code, and research workflows to ensure reproducibility.
• Assist with general research activities, including team meetings, progress updates, and project coordination tasks.
• Additional duties as assigned.

What This Job Offers

• Job Type: Part-time
• Career Level: Intern
• Education Level: High school or GED
• Number of Employees: 1,001-5,000 employees