Oncology Clinical Researcher
Job Description
Your expertise in oncology is vital to developing AI that can accelerate cancer research and improve patient outcomes. As an Oncology Clinical Researcher, you will play a pivotal role in validating and refining AI's understanding of complex clinical trial data, immunotherapy advancements, and cutting-edge cancer research methodologies.
Key Responsibilities
Critically evaluate AI-generated summaries and analyses of oncology clinical trial protocols, results, and adverse events.
Develop high-quality training data focused on specific cancer types, treatment modalities (e.g., CAR T-cell therapy, checkpoint inhibitors), and biomarker analysis.
Assess AI's ability to interpret complex genomic and proteomic data relevant to cancer research.
Provide expert feedback on AI outputs concerning drug development pipelines, regulatory submissions (e.g., IND, NDA), and post-market surveillance in oncology.
Create detailed evaluations and explanations for AI on the nuances of cancer staging, prognosis, and treatment guidelines (e.g., NCCN).
Identify and correct factual inaccuracies or logical inconsistencies in AI's understanding of cancer biology and therapeutic mechanisms.
Ideal Qualifications
MD or Ph.D. in Oncology, Cancer Biology, or a closely related field.
3• years of experience in clinical oncology research, preferably involving clinical trials.
In-depth knowledge of immunotherapy mechanisms, targeted therapies, and chemotherapy regimens.
Familiarity with clinical trial phases (I-IV), statistical analysis methods, and regulatory requirements.
Proficiency in interpreting scientific literature, including high-impact oncology journals.
Experience with real-world data (RWD) and real-world evidence (RWE) in oncology is a plus.
Project Timeline
Start Date: As soon as possible
Duration: Long-term engagement
• Commitment: Part-time, 20-30 hours/week
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