Alignerr
Oncology Clinical Researcher
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Oncology Clinical Researcher (AI Training)
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
Responsibilities
- Review and evaluate AI-generated oncology content for clinical accuracy, scientific validity, and regulatory alignment
- Apply your expertise in clinical trial design — including 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, covering 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
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Requirements
- Experienced in designing and managing oncology clinical trials from protocol development through to data readout
- Strong background in analyzing oncology clinical data — including 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
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Nice to Have
- Experience with data annotation, data quality assurance, or AI evaluation workflows
- Background in oncology subspecialties, such as:
- Immuno-oncology
- Hematologic malignancies
- Solid tumors
- Familiarity with clinical decision-making tools or real-world evidence frameworks
- Experience contributing to FDA/EMA submissions or peer-reviewed oncology publications
Benefits
- 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
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