Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- Working student position for AI & ML Engineer at Fraunhofer HHI. Involves developing AI-driven design platforms for architectural projects.
Responsibilities
- Design and train deep learning models (CNNs, GNNs) to generate 2D floor plans
- Expand our data pipelines — from ingesting architectural drawings through preprocessing and augmentation to label creation and versioning
- Apply mathematical and analytical thinking to solve complex spatial and geometric challenges
- Write reliable, well-structured code and optimize the performance of our tools and prototypes
- Test new methods, run experiments, and contribute ideas to improve our models and products
Requirements
- You are currently a student (B.Sc./M.Sc.) in Computer Science, Machine Learning, Data Science, or a related field at a university in Berlin or Brandenburg
- Solid knowledge of Python and practical experience with PyTorch or similar deep learning frameworks
- Familiarity with GPU workflows and distributed training setups
- Experience in preprocessing, augmentation, and dataset organization; confident use of NumPy and Pandas
- Ability to identify and troubleshoot issues in training and inference pipelines
- Clear communicator with a desire to collaborate in a dynamic startup environment
- You read research papers, reproduce experiments, and translate findings into working code
- Fluent English skills (German is a plus but not required)
Benefits
- Extremely interesting challenges in a research-driven and entrepreneurial environment
- Attractive salary
- Modern, well-equipped workplace in a central location
- Positive and highly collaborative working atmosphere within an international team
- Flexible working hours
- Remote work options
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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