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About the Role
This role supports a research project focused on AI-assisted surgical planning for orthopedic surgery, involving 3D reconstruction from 2D X-ray images to enhance surgical planning accuracy and efficiency.
Responsibilities
- Develop end-to-end deep learning pipelines for medical image segmentation and neural implicit representations.
- Contribute to data preprocessing, implementing training workflows, and validating model performance.
- Implement own ideas and contribute to scientific experiments and research publications.
- Create data visualizations and analyses to communicate results and track research progress.
Requirements
- Enrollment in Mathematics, Computer Science, or a related field.
- Solid programming skills in Python.
- Experience with CUDA.
- Good background in machine learning and computer vision.
- Good communication skills.
- Ability to work effectively in a collaborative and interdisciplinary team.
Skills
- Python
- CUDA
- Machine Learning
- Computer Vision
- PyTorch
- Medical Imaging
- Data Visualization
Location
- On-site at ZIB
Work Type
- Part-time
- Hybrid
Experience Level
- Student Assistant
Education Level
- Enrollment in Mathematics, Computer Science or a related field
Salary/Compensations
- Berlin state minimum wage (€14.84/hour) + capital allowance
Benefits
- Flexible scheduling of working hours
- Opportunity to combine the position with Master’s thesis or other academic work
- International and inspiring work environment
- Opportunities for professional and personal development
About the Company
- The Zuse Institute Berlin (ZIB) is an interdisciplinary research institute of the State of Berlin, combining artificial intelligence and scientific computing with applied mathematics and high-performance computing.
- ZIB develops computational methods to address challenges of societal relevance and provides state-of-the-art infrastructure for high-performance computing, artificial intelligence and data management.
Equal Opportunity
- The Zuse Institute Berlin (ZIB) is committed to diversity, equal opportunities, and a respectful and inclusive working environment.
- We expressly encourage women to apply to increase the proportion of women in underrepresented areas.
- We welcome applications from all qualified candidates regardless of age, disability, ethnic or social background, religion or belief, sexual orientation, or gender identity.