PhD Candidate in 3D Egocentric Vision

Job summary

This position offers a PhD scholarship focused on 3D egocentric vision and spatial AI, aimed at developing methods for intelligent systems to understand three-dimensional environments through egocentric observations. The candidate will engage in cutting-edge research within a collaborative environment at a leading technical university.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent academic level.
• Strong background in computer vision and machine learning.
• Experience with deep-learning frameworks such as PyTorch.
• Proficient in programming and debugging with Python and/or C++.
• Familiarity with Linux and software-development tools like Git, Conda, or Docker.
• Excellent written and spoken English skills.

Responsibilities

• Conduct research and develop innovative methods for 3D egocentric perception and spatial AI.
• Design, implement, and evaluate machine-learning models.
• Publish research findings in top-tier international conferences and journals.
• Collaborate with researchers at the university and partner institutions.
• Supervise BSc and MSc student projects.
• Participate in research-group activities and relevant teaching or dissemination tasks.

Skills

• Knowledge in 3D computer vision, point-cloud processing, or 3D reconstruction is advantageous.
• Experience in video understanding, egocentric vision, or multimodal learning is a plus.
• Familiarity with robotics, embodied AI, or continual learning is beneficial.
• Previous publication experience in computer vision, machine learning, or robotics is preferred.

Education

• A master's degree in a relevant field is required.

Tools

• Proficiency in deep-learning frameworks (e.g., PyTorch), programming languages (Python, C++), and software-development tools (Git, Conda, Docker) is essential.