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What if you could use AI to unlock valuable medical information hidden in thousands of documents and help turn it into insights that improve healthcare?
At SOPHiA GENETICS, we are building the future of AI-assisted, data-driven medicine. Our technology helps healthcare professionals make sense of complex data, with the ambition of improving outcomes for patients with cancer and rare diseases.
Every day, hospitals generate enormous amounts of valuable clinical information — diagnoses, treatments, biomarkers, imaging results and more. But much of this information remains locked inside PDF reports, making it difficult to analyze and use for research and innovation.
That's where you come in.
Join us for a six-month internship and explore how Large Language Models (LLMs) can transform unstructured medical reports into reliable, structured data that could support real-world evidence, clinical research and future AI applications.
What you'll work on:
You'll contribute to a real proof-of-concept project, exploring how different LLMs can extract clinical information accurately, efficiently and at scale.
Here's what that could look like:
You'll get to work at the intersection of AI, data science, data engineering and healthcare, tackling challenges that matter beyond a research experiment.
Requirements
You might be studying Data Science, Artificial Intelligence, Computer Science, Data Engineering or a related field.
You'll probably enjoy this internship if:
You don't need to know everything about medical AI already. We're looking for someone who is curious, rigorous and excited to explore how emerging technologies can solve real problems.
Benefits
What you'll get as part of a team?
An internship at SOPHiA GENETICS is not about watching from the sidelines. From day one, you're part of the team.
Duration: 6 months
All SOPHiA GENETICS internships and apprenticeships are paid according to each country's best practices and degree level.
Ready to put AI to work in healthcare?
Apply with your CV and any supporting information you'd like us to consider.
Bring your curiosity, challenge the models and help us explore how AI can turn complex medical data into meaningful insights.
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