Master Thesis AI Based Prediction for Anatomical Motion Modelling on Unity (AI)

Location: hirify.global office, Stockholm, Sweden

Company

hirify.global develops precision radiation medicine and radiotherapy solutions, including the Unity MR-Linac platform, used by healthcare providers in more than 130 countries.

What you will do

• Curate a dataset of target centroid motion from respiratory-influenced anatomies using public datasets and historical MR-Linac treatment data.
• Establish a benchmark by evaluating the existing prediction algorithm on the curated dataset.
• Select, adapt, and train an AI model to predict centroid motion at clinically relevant prediction horizons.
• Compare the proposed approach with the existing prediction algorithm using quantitative metrics.
• Deliver an assessment of AI-based motion prediction for the Automatic Position Management framework.
• Produce prototype software, reproducible processing pipelines, documentation, a written report, and a final presentation.

Requirements

• Master’s student in medical physics, computer science, applied mathematics, engineering physics, or a related scientific discipline.
• Programming experience and the ability to work independently on an exploratory research problem.
• Strong scientific or engineering background with confidence in quantitative analysis.

Nice to have

• Experience in medical image processing, ideally using Python.
• Experience with AI or deep learning methods.
• Familiarity with radiotherapy, especially MR-Linac systems.

Culture & Benefits

• Full-time master thesis project based at the hirify.global office in Stockholm.
• Flexible start date.
• Supervision by Ned Goodwin.