Oncologists; STfor AI Healthcare Research; MDT Task

We are seeking oncology registrars (ST3-7) based in the UK to help critique and improve oncology‑specific AI models. You will work asynchronously on curated, de‑identified patient cases—summarising each case as though you were preparing for a Multidisciplinary Team Meeting (MDT) using transcribed clinical notes and summaries.

• Cancer Types & Focus Areas: Solid tumors with emphasis on Hepatic, Brain, Pancreatic cancers and NSCLC.

• Clinical Case Analysis & MDT Summarisation: Analyse patient clinical notes and generate standardised summaries. Extract and summarise key information from Multidisciplinary Team (MDT) meeting transcripts, forming clear and concise summaries.

• Treatment Plan Summaries: Create structured treatment summaries using both clinical notes and MDT transcripts, ensuring clarity and completeness of all key information.

• Rubric & Scoring Guide Development: Design evaluation and scoring criterias based on patient and treatment summaries.

• AI Model Evaluation: Assess the quality of AI-generated summaries for both MDT and treatment plans against established criteria and guidelines.

• Clinical Guideline Compliance: Evaluate clinician treatment decisions adhere to relevant guidelines for cancer types. Validate the accuracy of AI-generated assessments of clinicians compliance to relevant guidelines.

• Medical registration: Current, Full license to practice and on GMC Register

• Clinical experience: Oncologist ST3 to ST7 practicing in the UK

• 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.

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

• You will work as an independent contractor.

• 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 (£60/hr).

• Professional Development: Gain hands‑on experience in data quality, structured data modeling, and medical informatics, with training provided on advanced labelling methodologies.

Do you know someone whose expertise might be a match for this project? Refer an expert and receive £100 if your referral completes a minimum of 10 hours of work.