Join REDI as a Medical Copy Editor Advancing Early Cancer Detection

About the Role: The Ratner Early Detection Initiative (REDI) seeks an experienced medical copy editor to support our ongoing research and policy work in early cancer detection. This is a regular part-time position for someone who combines meticulous attention to detail with a deep understanding of oncology literature and early detection science. Primary Responsibilities: • Edit white papers, journal articles, and policy documents focused on early cancer detection, AI-enhanced screening technologies, and CBC-based machine learning applications • Verify accuracy of every citation against original sources using medical databases (PubMed, Cochrane Library, etc.) • Fact-check clinical data, statistical claims, and research findings against primary literature • Review and improve AI-generated content to ensure scientific accuracy, appropriate tone, and elimination of hallucinations or fabricated references • Ensure consistency in terminology, formatting, and citation style across documents • Flag any scientific or logical inconsistencies in arguments or data interpretation • Prepare manuscripts for journal submission, ensuring compliance with target journal requirements Required Qualifications: • Advanced degree (MS, PhD, MD, or equivalent) in oncology, public health, epidemiology, or related field, OR extensive professional experience in medical editing/writing in oncology • Full working knowledge of major AI language models, including Claude, ChatGPT, and Gemini – must understand their capabilities, limitations, and common error patterns • Proven experience editing peer-reviewed medical literature, particularly in cancer screening, early detection, or related fields • Expert knowledge of major citation styles (AMA, APA, Vancouver) • Proficiency with citation management systems (EndNote, Zotero, Mendeley, etc.) • Demonstrated experience identifying and correcting AI-generated content issues, including hallucinated references, fabricated studies, and inappropriate synthesis • Demonstrated ability to verify complex medical and statistical claims against primary sources • Excellent understanding of research methodology and biostatistics Strongly Preferred: • Familiarity with machine learning/AI applications in healthcare • Experience with hematology and complete blood count (CBC) analysis • Knowledge of health policy, healthcare economics, or health disparities research • Previous work with healthcare systems, academic medical centers, or research institutions • Experience using AI tools productively while maintaining scientific rigor About Our Work: You'll be editing content on cutting-edge topics, including CBC-based AI cancer detection, mobile screening initiatives, risk stratification programs, and cost-effectiveness analyses of early detection technologies. Our work involves collaboration with major healthcare systems, including Mayo Clinic, Mercy Hospital, and Weill Cornell Medicine. Work Arrangement: • Part-time, ongoing position (approximately 10-20 hours per week, flexible based on project flow) • Remote work acceptable • Compensation commensurate with experience • Projects include both shorter white papers and longer comprehensive analyses requiring deep fact-checking To Apply, please submit: 1. Resume/CV highlighting relevant medical editing experience 2. Cover letter describing your experience with oncology literature, reference verification, and working with AI-generated content 3. Two samples of medical editing work (before/after if possible, with identifying information redacted) 4. Three professional references Apply tot his job