Internship AI & Large Language Models (LLM Project)

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Amsterdam Health & Technology Institute (ahti) is looking for an AI / Computer Science / Data Science intern

The Netherlands has a strong healthcare system, but there is always room for improvement. At ahti, our mission is to enhance health, well-being, and access to care. We believe that data can play a vital role in strengthening the Dutch healthcare system and reducing inequalities. Our focus is on achieving better outcomes for individual residents as well as for the system as a whole, with particular attention to reducing inequality.

Does our mission energize you? Are you passionate about artificial intelligence and large language models (LLMs)? Do you want to apply your skills to real-world challenges in health and data science? Then you are the motivated intern in AI / Computer Science / Data Science that ahti is looking for.

In this internship you will contribute to the development of an innovative assistant that helps researchers and analysts by interpreting complex questions and generating high-level analysis strategies. The project is focused on combining LLMs with domain-specific knowledge, advancing the way we work with healthcare and research data.

Your internship will take place at our offices located at the Amsterdam Health and Technology Center (AHTC), where we are part of the health tech community, with the possibility to work partly remote. We are looking for someone who is available from October 2025 for a period of 3–4 months. During this internship, you will:

  • Develop a specialized LLM solution that:
    • Integrates with a domain-specific knowledge base derived from structured and unstructured technical documentation (PDF guides and existing code/pseudo-code).
    • Can translate research questions into suggested analysis strategies and pseudo-code, including relevant data sources, variables, data transformations, and summary operations.
  • Design and implement a Retrieval-Augmented Generation (RAG) pipeline to support accurate, context-aware model outputs.
  • Contribute to the scalability of the solution, for example by deploying it through an API or lightweight interface.

We are looking for a team member who brings curiosity, creativity and technical expertise. You recognize yourself in the following:

  • Solid understanding of LLMs and recent AI developments.
  • Experience with Retrieval-Augmented Generation (RAG) frameworks.
  • Skilled in Python (preferred) or R.
  • Familiarity with data analysis pipelines, including joins, aggregations, and pre- and post-processing steps – such as calculating aggregations or summary statistics
  • Comfortable working with large collections of technical or semi-structured documents (PDF).
  • Ability to work independently, collaborate effectively, and communicate complex ideas clearly

What You’ll Gain

  • Real-world experience developing and scaling applied LLM solutions
  • Exposure to modern NLP techniques and tools in a practical context
  • Mentorship from experienced data scientists
  • Opportunity to work on an applied project in a supportive and intellectually curious team

About Ahti’s Team

Our team brings together a wide range of expertise. Some of us are data analysts, others have backgrounds in economics or econometrics, and many have extensive experience in healthcare. We collaborate on projects and work closely to further develop ahti’s impact.

Beyond our work at ahti, several colleagues are also active as healthcare professionals, entrepreneurs, or academic researchers. This mix of backgrounds and perspectives creates a dynamic and inspiring environment to work in.

Interested?

Great! Then let’s get to know one another soon. We believe a conversation is the quickest way to see if we’re a good match. Send an email to carriere@ahti.nl with your CV and a short introduction, and we’ll schedule a phone call, a Teams meeting, or an in-person chat over coffee—whatever suits you best!

Applications are reviewed on a rolling basis and the vacancy will be closed as soon as a suitable candidate has been identified.