Cardiac AI Research Engineer

Cardiac AI Research Engineer

Materialise

Ghent, Belgium

We're seeking a Cardiac AI Research Engineer to help create the next generation of AI-powered, patient-specific preoperative planning tools for structural heart interventions. In this role, you’ll combine deep learning expertise with medical image analysis to turn innovative ideas into solutions that improve patient outcomes. You’ll work closely with multidisciplinary teams, internal stakeholders, and external partners to bring your algorithms from research to real-world clinical and workflow deployment. 

What you will do

• Design, implement, and validate algorithms and deep learning models for 3D cardiac CT and related medical imaging data;
• Collaborate with internal and external stakeholders to define requirements, propose solutions, and ensure clinical relevance;
• Document research workflows, results, and performance metrics in compliance with medical software standards;
• Optimize algorithms for patient-specific planning and medical image processing tasks;
• Validate model performance and communicate findings to stakeholders;
• Work with cross-functional teams to integrate and deploy algorithms in clinical workflows;
• Stay current with developments in AI, medical imaging, and related technologies, proactively introducing new ideas to the team.

Your profile

• Master’s degree in biomedical engineering, computer science, electrical engineering, or a related field;
• 3+ years of professional hands-on experience in machine learning/deep learning, preferably using PyTorch;
• Proficiency in Python and relevant data science frameworks (e.g., MONAI, PyTorch Lightning, NumPy, Pandas);
• Strong analytical, problem-solving, and communication skills;
• Fluent in English, both written and verbal;
• Able to work independently and collaboratively in a multidisciplinary team;
• Experience within a DevOps ecosystem (Git, CI/CD, Docker, etc.).

Preferred:

• Experience with medical image segmentation, cardiac imaging, or structural heart planning
• Familiarity with cloud computing platforms (AWS, Azure, GCP)
• Understanding of Agile development practices
• Experience with deploying AI models in clinical environments