Machine Learning Student, (MSc Students)

Make a meaningful difference to patients around the world.

Our University Programs are designed to help early-career professionals contribute to solutions that transform patient lives. We also believe in investing in the future of our talented people across the globe, including early career professionals seeking to explore and establish themselves within the medical device industry.

We’ll provide you with the opportunity to thrive in a dynamic environment where you can make innovative contributions. As a R&D Student, you’ll find motivation and inspiration in a culture that emphasizes passion for patients as you discover your own strengths.

We are seeking a motivated MSc student to join our R&D team as a Machine Learning Engineer focusing on medical image processing (CT, MRI). In this role, you will support the development and optimization of deep learning models for image segmentation and analysis, leveraging U-Net and 3D U-Net architectures.

This is a hands-on opportunity to work on real-world clinical data and contribute to next-generation solutions for diagnostic and procedural planning workflows.

How you will make an impact:

• Model Development:
• Assist in designing and implementing deep learning models for medical image segmentation using U-Net, 3D U-Net, and nnU-Net frameworks.
• Support optimization of models for volumetric CT/MRI datasets.
• Data Handling & Processing:
• Develop preprocessing pipelines (normalization, augmentation, resampling).
• Integration & Experimentation:
• Support integration of models into research pipelines using tools like MONAI and 3D Slicer.
• Run experiments, evaluate model performance, and document results.
• Collaboration:
• Work closely with engineers, data scientists, and clinical teams.
• Participate in technical discussions and contribute ideas for improving model performance.
• Research & Innovation:
• Stay updated on state-of-the-art methods in medical imaging AI and segmentation.
• Explore improvements in model architecture and training strategies.
  
  

• MSc student in Computer Science, Electrical Engineering, Biomedical Engineering, or related field - Must
• Strong programming skills in Python with production-level coding standards
• Proven hands-on experience with TensorFlow and PyTorch
• Strong background in machine learning and deep learning
• Experience in computer vision-based algorithm development
• Knowledge of advanced data science and model optimization techniques
• Excellent problem-solving and analytical skills with a focus on innovation