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