Working Student - Machine Learning
Core
Researching efficient on-device machine learning for augmented reality glasses using event-based sensing and embedded processors.
Role type
Working Student - Machine Learning (Thesis)
Builds
Next-generation AR glasses (Spectacles) with real-time, low-power perception capabilities.
Domain
Augmented Reality / Embedded Systems / Edge AI
Deliverable
Research
Required skills
Deep learning, Event-based sensing, Embedded systems, Model optimization, System architecture
Preferred skills
Experience with low-power hardware, Real-time processing, Co-design of models and systems
Technologies
Neural networks, Event-driven processors, Embedded hardware
Responsibilities
Architect models for accuracy and ultra-efficiency on event-driven hardware, Analyze trade-offs between accuracy, latency, memory, and energy, Transform research ideas into practical improvements on realistic platforms.
Seniority
Student (Thesis)
