Overview
ETH Zurich, a prestigious institution known for its contributions to science and technology, is currently offering PhD positions in the field of geometric deep learning. This opportunity is particularly significant for those interested in advancing their research in image and point cloud processing, an area that is gaining traction in the AI/ML community.
Background & Relevance
Geometric deep learning is an emerging field that focuses on extending deep learning techniques to non-Euclidean domains such as graphs and manifolds. This research is crucial for applications that involve complex data structures, such as 3D models and point clouds. As industries increasingly rely on advanced data analysis methods, expertise in this area is becoming essential for tackling real-world challenges in computer vision and remote sensing.
Key Details
- Position: 2 PhD candidates (100%) in geometric deep learning for image and point cloud processing
- Location: ETH Zurich, Switzerland
- Collaboration: Between the EcoVision Lab and the Data Analytics Lab
- Research Focus: Developing methods to analyze non-grid structured data for predicting 3D CAD models from unstructured 3D point clouds and generating topographic maps from 2D images
- Experience: Prior knowledge in machine learning, computer vision, and remote sensing is advantageous
- Language Requirement: Fluency in English (written and spoken) is mandatory
- Application Link: Apply Here
Eligibility & Participation
These PhD positions are open to candidates who have a strong academic background in relevant fields such as computer science, engineering, or mathematics. The roles are designed for individuals who are enthusiastic about research and are eager to contribute to innovative projects in geometric deep learning.
Submission or Application Guidelines
Interested candidates should follow these steps to apply:
1. Visit the application link provided.
2. Prepare your application materials, including a CV and cover letter.
3. Submit your application through the online portal as per the instructions outlined on the website.
Additional Context / Real-World Relevance
The research conducted in geometric deep learning has profound implications across various domains, including robotics, autonomous vehicles, and environmental monitoring. By focusing on the analysis of complex data structures, researchers can develop more accurate models and solutions that address pressing challenges in technology and science.
Conclusion
This is a remarkable opportunity for aspiring PhD candidates to join ETH Zurich and contribute to groundbreaking research in geometric deep learning. Interested individuals are encouraged to apply and explore the potential of their research in shaping the future of AI and machine learning.
Category: PhD & Postdoc Positions
Tags: geometric deep learning, eth zurich, machine learning, computer vision, data analytics, eco vision lab, 3d modeling, point cloud processing
