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  • Aptura

    United Kingdom

    • We are seeking qualified medical doctors to annotate and code clinical documents with SNOMED CT, with a focus on accuracy and consistency against detailed coding guidelines.

    You will work asynchronously on a dedicated annotation platform, coding de-identified clinical notes and documentation including discharge summaries, lab results and progress notes against SNOMED CT concepts to support the development of clinical AI platforms.

    This is a remote, flexible and short-term project.

    Key Responsibilities

    • Structured Annotation: Identify clinically relevant concepts across discharge summaries, lab results and prognosis notes, and map them to the correct SNOMED CT codes on a dedicated platform.

    • Guideline Application: Work to a coding guideline covering hierarchy scope, negation, medication scope, section-level inclusions and compound coding, applied consistently across a large volume of documents.

    • Edge Case Handling: Flag ambiguous or contested cases with a short rationale so guidance can be refined.

    • Quality Review: Participate in adjudication rounds to resolve disagreements and reach a consensus code set.

    Qualifications:

    License: GMC Registered Doctor based in the UK

    Experience: Minimum 1–2 years of clinical practice, with SNOMED CT coding or clinical terminology experience.

    Knowledge: Strong grounding in clinical documentation, terminology and coding conventions.

    Attention to detail: Proven accuracy and consistency in coding or clinical review work.

    Technical proficiency: Comfortable using structured annotation tools and digital platforms.

    Language: Native or near-native written English.

    Legal Status

    You will have the right to work in your country of residence.

    You will work as an independent contractor.

    Why Join Us?

    • Flexible Work Arrangements: Part-time, remote and fully asynchronous.

    • Competitive Compensation: Hourly rate, paid weekly

    • Professional Development: Hands-on experience in clinical AI development and terminology work, shaping how AI systems interpret clinical records and assign medical codes.

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