Oncologists for MDT Task based Work
Remote
Hourly contract
£50+ per hour
We are seeking oncology registrars based in Europe to help critique and improve oncology‑specific AI models. You will work asynchronously on curated, de‑identified (or fully synthetic) patient cases—summarising each case as though you were preparing for a Multidisciplinary Team Meeting (MDT).
Key Responsibilities
Clinical case review: Analyse patient records (clinical notes, pathology, imaging, genomics, investigations and previous management).
Simulated decision‑making:
- Formulate differentials/impressions with relevant disease staging.
- Draft management plans grounded in current guidelines.
Structured documentation: Produce clear, structured case summaries and rationales suitable for AI model evaluation and training.
Mock MDT preparation (async): Submit written MDT briefs.
Quality & governance: Apply NICE, ESMO, NCCN (or local) guidelines.
Qualifications
- Medical registration: Current, unrestricted licence in an EU/EEA member state or UK (e.g. GMC Specialist Register, IMC, CNOM, Ärztekammer).
- Clinical experience: Oncologist (ST3+) or non-UK equivalent (3 years+ of specialist experience).
- Language: Professional working English for written deliverables.
- Relevant experience: The ideal candidate is able to simulate clinical decision-making as the oncologist (e.g. formulating diagnoses, staging disease, and outlining treatment plans). Furthermore, they are proficient in writing clear case summaries, developing patient management plans, and preparing for mock MDTs.
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 and remote work options available (10–30 hours a week).
- Competitive Compensation: Hourly compensation in line with level of clinical experience (£50+/hr).
- Professional Development: Gain hands-on experience in data quality, structured data modeling, and medical informatics, with training provided on advanced labeling methodologies.
