AI/Machine Learning Research Intern (m/f/x)

DoctolibParis, Paris, France

On-site Internship

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Experience Level

Entry Level

Qualifications

What We Are Looking ForIf the profile described below does not exactly match your qualifications but you believe this job aligns with your skills and aspirations, we encourage you to apply anyway. You might be our next team member if you:Are proficient in Python and the data processing ecosystem (pandas, scikit-learn)Are familiar with language models and associated libraries (HuggingFace Transformers, vLLM, or equivalent)Possess excellent scientific writing skills in both French and EnglishAre nearing the completion of a Master’s degree (either professional or research) or an engineering schoolShow a strong interest in issues of equity and bias in AI

About the job

Join Our Team

At Doctolib, we are on a mission to revolutionize healthcare access and enhance the quality of life for healthcare professionals. As a part of our commitment to responsible artificial intelligence, we are seeking a Master’s level intern to assess biases in a pediatric dialogue system by analyzing interactions between AI and patients.

Collaborating with Doctolib's data scientists and researchers from LISN (Université Paris-Saclay), you will help ensure fairness and reliability in our AI health solutions. One of the key objectives of this internship is to create an annotated and anonymized dataset that will be published as open-source. This five-month internship will allow you to work on a project with significant societal impact, at the intersection of natural language processing, health, and AI ethics.

Your responsibilities will include:

Conducting a literature review on bias assessment methods in health-related language models
Analyzing a corpus of anonymized dialogues between the AI system and pediatric patients/parents to identify potential biases
Defining and implementing an annotation scheme to characterize identified biases
Building an evaluation framework based on demographic characteristic disaggregation
Applying this framework to the dialogue system and comparing results with other autoregressive models

About Doctolib

Doctolib is a leading digital health service provider in Europe, dedicated to improving access to healthcare and enhancing the quality of life for healthcare professionals. We are committed to leveraging technology to create innovative solutions that empower both patients and medical practitioners.

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