Oncology Clinical Researcher
About this role
About the Role What if your deep expertise in cancer clinical trials could directly shape how AI reasons about oncology — influencing systems that may one day support life-saving treatment decisions for patients worldwide? We're looking for Oncology Clinical Researchers to bring real-world clinical rigor into the AI training pipeline. You'll review, evaluate, and improve AI-generated oncology content — ensuring that the models being built today reflect the scientific, regulatory, and clinical standards that matter most in cancer medicine. This is a fully remote, flexible contract role. No AI background needed — just serious oncology expertise and a sharp eye for clinical accuracy. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Review and evaluate AI-generated oncology content for clinical accuracy, scientific validity, and regulatory alignment - Apply your expertise in clinical trial design — protocol development, patient enrollment, endpoints, and safety monitoring — to assess how well AI systems understand real-world trial methodology - Analyze AI outputs related to cancer trial data, including efficacy results, safety profiles, and biomarker findings - Evaluate AI-generated regulatory and scientific content against FDA/EMA submission standards - Provide structured, expert feedback that directly shapes how AI models reason about oncology - Work independently and asynchronously — fully on your own schedule Who You Are - Experienced in designing and managing oncology clinical trials from protocol development through data readout - Strong background in analyzing oncology clinical data — endpoints, safety profiles, biomarkers, and statistical outputs - Solid familiarity with regulatory standards for agencies such as the FDA or EMA - Detail-oriented and methodical — you catch what others miss - Able to translate complex clinical knowledge into clear, structured evaluations - No prior AI or data annotation experience required Nice to Have - Experience with data annotation, data quality assurance, or AI evaluation workflows - Background in oncology subspecialties such as immuno-oncology, hematologic malignancies, or solid tumors - Familiarity with clinical decision-making tools or real-world evidence frameworks - Experience contributing to FDA/EMA submissions or peer-reviewed oncology publications Why Join Us - Work directly on frontier AI systems being built to transform cancer research and clinical medicine - Influence how AI models understand and reason about real oncology data — at the cutting edge of the field - Fully remote and flexible — work when and where it suits you - Freelance autonomy: set your own pace, choose your hours, collaborate globally - Meaningful work with real-world impact on how AI approaches one of medicine's hardest problems - Potential for ongoing work and contract extension as new projects launch
Application listings
Choose a source listing and check its country requirements.