Model à Grande-Bretagne

Are you passionate about medical imaging and AI? We are looking for a motivated and curious Intern to join our research / engineering team working at the intersection of neuroscience, medical imaging, and deep learning.

As an intern, you will contribute to cutting-edge research involving MRI image analysis using deep learning techniques in Python. You will gain hands-on experience with real-world neuroimaging datasets, work with expert mentors, and contribute to impactful projects aimed at advancing medical diagnosis and understanding brain disorders.

1. Preprocess MRI data
2. Develop and apply deep learning models (e.g., CNNs, U-Nets) for image segmentation, classification, or synthesis tasks
3. Perform model evaluation, interpretability analysis, and data visualization
4. Collaborate with researchers to validate findings and refine model performance
5. Python programming: Solid understanding and experience with scientific libraries (NumPy, Pandas, Matplotlib)
6. Deep learning: Familiarity with frameworks such as PyTorch or TensorFlow
7. Version control: Experience using Git / GitHub for collaborative development

Nice to have:

1. Experience working with MRI images / images
2. Prior experience with segmentation networks (e.g., U-Net, nnU-Net)
3. Familiarity with libraries such as MONAI, or SimpleITK
4. Exposure to containerization tools like Docker
5. Understanding of statistical analysis or machine learning evaluation metrics

What our employees value

• Innovation and internationality – a forward-looking infrastructure, modern laboratory and office equipment, software tools, and the opportunity for international exchange with colleagues from 65 nations
• Family-conscious corporate culture – because we know that family is important
• Health promotion – through our extensive range of company health programs
• Individual onboarding – to ensure a smooth start in your new professional challenge
• The position is limited to 3 to 6 months

Please send your CV, a brief statement of interest, and (if available) a GitHub portfolio or sample project to arnab.bandyopadhyay@dzne.de