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💼 Full-time🗓 2026-06-25

Core

Develop and test NLP models to detect bias, tone-policing, and equity violations in real-world healthcare review data.

Role type

NLP Research Fellow (Intern)

Builds

Bias detection systems and accountability tools for healthcare equity analytics

Domain

Healthcare + Natural Language Processing

Deliverable

production ML models

Required skills

Python, Hugging Face Transformers, spaCy, NLTK, zero-shot/few-shot classification, prompt engineering, model evaluation (sensitivity, specificity, fairness metrics), explainability tools (SHAP, LIME)

Preferred skills

Experience with MIMIC-III, Bias in Bios, or HealthReviewCorpus datasets, background in fairness or social impact

Technologies

Python, Hugging Face, spaCy, NLTK, SHAP, LIME

Responsibilities

Develop and test zero-shot and few-shot NLP models to flag bias and equity violations; Clean and label real-world review data from platforms like Google, RateMDs, Vitals, Healthgrades; Evaluate models for fairness metrics and false positives; Create explainability tools to make outputs auditable

Seniority

Intern

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