Remote Oncology Clinical Researcher for AI Training

Alignerr Corp.; Glasgow; Remote; GBP 55,000 - 96,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Task-based freelance work

Job summary

Alignerr Corp. is seeking an Oncology Clinical Researcher to guide AI training with deep oncology trial expertise. This fully remote, hourly contract role focuses on bringing real-world clinical science into AI development for cancer research.

The candidate will design and evaluate protocols, analyze trial data, and ensure regulatory alignment for AI-derived outputs. Strong independence and rigor are essential.

Qualifications

• Experience in designing and managing oncology clinical trials from protocol development to data readout.
• Strong analytical background in oncology data, endpoints, safety, and biomarkers.
• Familiar with regulatory submission standards (FDA/EMA).
• Detail-oriented and methodical with scientific rigor.
• Ability to work independently and deliver high-quality evaluations.

Responsibilities

• Design and evaluate oncology trial protocols, including enrollment criteria, endpoints, and regulatory compliance.
• Analyze cancer trial data—safety, efficacy, biomarkers—to assess treatment performance and relevance.
• Translate trial outcomes into outputs aligned with regulatory submission standards (FDA/EMA).
• Review AI-generated oncology content for scientific validity and regulatory alignment.
• Identify gaps and inconsistencies in how AI models interpret oncology research.

Skills

Oncology trial design

Data analysis

Regulatory standards

Attention to detail

Independent work

Tools

Data annotation

Job description

Alignerr Corp. is seeking an Oncology Clinical Researcher to guide AI training with deep oncology trial expertise. This fully remote, hourly contract role focuses on bringing real-world clinical science into AI development for cancer research.

The candidate will design and evaluate protocols, analyze trial data, and ensure regulatory alignment for AI-derived outputs. Strong independence and rigor are essential.