PhD - Cross-Domain Hyperspectral Anomaly Detection for Manufacturing (f/m/div.)
Tasks
- Apply domain generalization
- Apply self supervised representation learning
- Collaborate with research partners to transfer results
- Develop and evaluate machine learning models
- Develop data efficient and scalable methods
- Develop hyperspectral anomaly detection methods
- Present at international conferences
- Process hyperspectral data
- Publish research in scientific journals
- Use transfer learning and meta learning
Perks/Benefits
- N/A
Skills/Tech-stack
Computer Vision | Data Efficient Methods | Deep learning | Hyperspectral Imaging | JAX | Machine Learning | Meta Learning | Probabilistic Modeling | PyTorch | Python | Representation Learning | Scalable systems | Self-Supervised Learning | Self-supervised | Supervised Learning | Transfer Learning
Education
Roles
Regions
Countries
States
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