How do I apply for the AI-Assisted Fracture Reduction Internship position at Materialise NV and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

Is the internship at Materialise NV paid and what compensation can candidates expect?

Yes, this is a paid internship opportunity. Exact compensation details are typically finalized during the company interview process.

What are the working arrangements and expected duration for the AI-Assisted Fracture Reduction Internship role?

This position is a not disclosed, structured as a hybrid role, with an expected duration of 4 months.

What educational background or degree level is required for the AI-Assisted Fracture Reduction Internship at Materialise NV?

Candidates are generally expected to be holding or pursuing the following degree levels: Master, PhD.

Does Materialise NV provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

AI-Assisted Fracture Reduction Internship

Materialise NV

Found 1 month ago

Location

Leuven, Belgium

Duration (Months)

4 Months

Time

Not disclosed

Work Mode

Hybrid

Salary

unpaid

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Master
PhD

Skills & Qualifications

Technical Skills

Python
Numpy
Scikit-learn
PyTorch
TensorFlow
3D geometry processing
statistical shape modeling
machine learning
3D reconstruction
object matching
pattern recognition

Soft Skills

puzzle-solving
problem-solving

Job Description

In this project, you will tackle challenging fracture cases, which often contain numerous bone fragments of varying sizes. Your mission will be to design and implement smart algorithms to identify fragments and solve the reduction puzzle. Solutions can be guided by patient-specific templates of the premorbid anatomy — reconstructed using statistical shape models for the relevant anatomy or advanced AI-based techniques, depending on your skills and interests. This is a unique opportunity to contribute directly to innovation in surgical planning tools that can improve patient outcomes in trauma cases.

Requirements

MSc or PhD in computer science, AI, data science, mathematics, statistics, physics, biomedical engineering, or another equivalent technical field
Experience with Python programming (including libraries such as Numpy, Scikit-learn, and deep learning frameworks like PyTorch or TensorFlow)
Background in 3D geometry processing
Understanding of statistical shape modeling or machine learning techniques for shape reconstruction is a strong plus
Experience with algorithms for 3D reconstruction, object matching, or pattern recognition
Working proficiency in English
The internship must be part of your degree program
Your university must provide an internship contract

Software Engineering

AI/ML/GenAI Engineering

Languages

English

Nice to Haves

statistical shape modeling
machine learning techniques for shape reconstruction

Apply Now

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