Oncology Clinical Researcher

Job summary

Review AI-generated oncology content for clinical accuracy, scientific validity, and regulatory alignment, including trial protocols, endpoints, safety, efficacy, and biomarkers. Provide structured expert annotations and assessments to improve AI model performance, working independently on flexible, task-based assignments.

Job details

Oncology Clinical Researcher (AI Training) About The Role What if your deep knowledge of cancer clinical trials could directly shape how AI understands and reasons about oncology — influencing the tools that will define the future of cancer research and treatment? We're looking for Oncology Clinical Researchers to bring real-world clinical expertise into AI-driven research and evaluation workflows. Your experience designing trials, analyzing data, and navigating regulatory standards will ensure that the AI systems being built today reflect the scientific rigor and clinical accuracy that oncology demands. This is a fully remote, flexible contract role — no relocation, no rigid schedule, just meaningful work on your own terms. 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 trial design expertise to assess how well AI models represent real-world oncology study protocols, endpoints, and enrollment standards Analyze AI outputs involving cancer trial data — including safety profiles, efficacy results, and biomarker interpretation — and provide structured expert feedback Evaluate AI-generated regulatory and scientific content against FDA, EMA, and ICH submission standards Translate your clinical knowledge into clear, actionable annotations and assessments that directly improve AI model performance Work independently and asynchronously on task-based assignments — fully on your own schedule Who You Are Experienced in designing and managing oncology clinical trials — from protocol development through data readout Strong analytical background in oncology clinical data, including primary and secondary endpoints, safety monitoring, and biomarker analysis Familiar with regulatory submission standards for major agencies such as the FDA or EMA Detail-oriented and systematic — you notice when clinical reasoning doesn't hold up Clear and precise written communicator able to document expert feedback in structured formats Self-motivated and reliable when working independently Nice to Have Prior experience with data annotation, data labeling, or AI evaluation workflows Background in translational oncology, biostatistics, or clinical pharmacology Experience contributing to regulatory submissions, clinical study reports, or scientific publications Familiarity with AI tools or research platforms as an end user Why Join Us Work directly on frontier AI systems being built to transform cancer research Influence how AI models understand, reason about, and communicate real oncology science Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, expert-driven work Collaborate with world-leading AI research teams and labs Potential for ongoing work and contract extension as new projects launch

What you’ll do

Review AI-generated oncology content for clinical accuracy, scientific validity, and regulatory alignment, including trial protocols, endpoints, safety, efficacy, and biomarkers. Provide structured expert annotations and assessments to improve AI model performance, working independently on flexible, task-based assignments.

Requirements

Candidates should have experience designing and managing oncology clinical trials, from protocol development through data readout, and strong analytical expertise in oncology clinical data. They should understand FDA or EMA regulatory standards, communicate precise written feedback, and work reliably and independently; experience in AI evaluation, annotation, translational oncology, biostatistics, or clinical pharmacology is an advantage.

Benefits

• Flexible Schedule
• Remote Work
• Freelance Autonomy
• Potential for Ongoing Work and Contract Extension

Listed skills

• safety monitoring · Preferred
• Regulatory Compliance · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Oncology Clinical Trial Design
• Clinical Trial Management
• Oncology Clinical Data Analysis
• Protocol Development
• Endpoint Assessment
• Safety Monitoring
• Biomarker Analysis
• Regulatory Compliance
• FDA Standards
• EMA Standards
• ICH Submission Standards
• AI Content Evaluation
• Data Annotation
• Scientific Writing
• Clinical Research
• Structured Feedback

Job areas

• Healthcare
• Science & Research
• Technology
• Data & Analytics

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