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
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Apply Now