About this role
Job SummaryThis position is located in the Agency for Toxic Substances and Disease Registry, headquartered in Atlanta, Georgia.
QualificationsApplicants must have: A background in environmental health, toxicology, public health, environmental science, or a related scientific field. Experience conducting scientific literature searches and critically evaluating published research. Familiarity with computational toxicology concepts, including QSAR, PBPK modeling, machine learning, and other computational approaches used to interpret toxicological data. Experience conducting systematic reviews, scoping reviews, or other structured evidence synthesis methods. Proficiency using reference management software (e.g., EndNote, Zotero, Mendeley, or similar). Strong scientific writing, technical communication, and analytical skills. Experience organizing, synthesizing, and summarizing complex scientific information from multiple sources. Preference may be given to applicants with: Knowledge of New Approach Methodologies (NAMs), including in vitro testing, omics technologies, organ-on-a-chip systems, and adverse outcome pathway (AOP) frameworks. Familiarity with environmental exposure assessment and risk assessment principles. Knowledge of regulatory frameworks related to chemical safety, environmental health, or toxicology. Experience identifying and evaluating open-source scientific tools, databases, and reproducible research workflows. Ability to work independently while collaborating effectively in a multidisciplinary scientific environment. Volunteers must meet the definition of a student defined as "an individual enrolled not less than half-time in a high school, trade school, technical or vocational institute, junior college, college, university, or other accredited educational institution (5 U.S.C. §3111(a) and 5 CFR §308.101)" throughout the duration of their volunteer service, except during acceptable breaks in education as described in 5 CFR §308.101.
Major DutiesWHAT YOU'LL BE DOING DAY TO DAY As a Student Volunteer you will use your knowledge of and experience with Computational Toxicology and New Approach Methodologies (NAM) to optimize business results and customer experience by: Conduct comprehensive literature searches on Computational Toxicology and NAMs related to the health effects of microplastics and Nano plastics. Perform systematic or scoping literature reviews using established review methodologies. Critically evaluate and synthesize scientific evidence on computational toxicology approaches, including quantitative structure-activity relationship (QSAR) models, physiologically based pharmacokinetic (PBPK) modeling, machine learning, and in silico exposure assessment methods. Review and summarize the application of NAMs, including in vitro methods, high-throughput screening, organ-on-a-chip technologies, omics approaches, and adverse outcome pathway (AOP) frameworks. Analyze scientific literature to identify strengths, limitations, research gaps, and opportunities for integrating computational and experimental methods for risk assessment. Organize, manage, and document scientific references using reference management software. Prepare clear, concise written summaries, evidence tables, and technical reports to communicate findings. Identify reproducible workflows, open-source tools, and publicly available data resources that support transparent and reproducible environmental health research. Collaborate with CDC scientists and multidisciplinary teams to support evidence synthesis and inform environmental and public health research priorities. Characterizing the current state of knowledge on the physicochemical properties of microplastics and nanoplastics that influence toxicity. Identifying how computational and alternative methods are being applied to model their behavior, fate, and biological interactions. Evaluating the strengths, limitations, and data gaps associated with these approaches. Highlighting opportunities for integrating computational models with experimental NAM data to improve risk assessment.