Research Assistant, Public Health-Social Sciences
Job Summary
Aid in the planning, development, implementation, evaluation, writing, and dissemination of the assigned project(s). This role integrates research management and academic research skills.
Key Responsibilities
Run statistical models for data validation, quality checks, and anomaly detection.
Identify inconsistent, flawed data using both classical and augmented techniques.
Support the development of a data-integrity scoring system for survey and behavioral data.
Contribute to best-practice standards, SOPs, and workflows for reproducible science.
Help design automated workflows that reduce researcher burden (e.g., data processing, QC pipelines, templated processes).
Test and refine generative-AI–informed tools for research support.
Build draft templates, protocols, and playbooks for early-career investigators.
Conduct literature scans and prepare summaries.
Assist with drafting manuscripts, reports, and presentations.
Collaborate with statisticians, programmers, and faculty to refine and test systems.
Contribute ideas for new research-support products.
Prototype and test new service offerings for faculty (e.g., protocols, automated onboarding workflows, integrated startup kits).
Engage creatively in forecasting what researchers will need 2–3 years from now.
Minimum Acceptable Qualifications
Master's degree with at least four years of relevant research experience, or an equivalent combination of education and experience.
Demonstrated knowledge of scientific principles.
Strong computer skills.
Strong communication skills.
Strong foundation in classical statistical methods and quantitative analysis.
Experience with data cleaning, data validation, and data management.
Demonstrated problem-solving ability and curiosity.
Strong writing, communication, and collaboration skills.
Additional Desirable Qualifications
Supervisory ability.
Experience beyond the minimum.
Teaching experience.
Public speaking experience.
Prior participation in the preparation of grant proposals.
Peer reviewed publications and/or oral or poster presentations at national meetings.
Interest or familiarity with AI tools, LLMs, or workflow automation.
Experience with R, Python, or similar statistical programming tools.
Ability to work in fast-paced, evolving, “startup” environments.
Creative mindset and comfort generating new ideas.