1. What are the limitations of existing Gaussian-based scene representations for sensor simulation, and how can they be extended to become sensor-ready?
2. Which semantic and physical attributes must be encoded in Gaussian primitives to enable flexible simulation of different sensor modalities?
3. How well can sensor-ready Gaussian representations support re-simulation of sensor data compared to real-world observations?
Studiengänge:
* Computer Science
* Artificial Intelligence
* Robotics
* Math, Data Science or comparable degree program
Studienschwerpunkte:
* Software development / programming
* Machine learning / deep learning
* Digital image processing
* Statistics / data science
Fachkenntnisse:
* Solid understanding of popular machine learning and deep learning concepts
* Experience with computer vision
* Experience with Gaussian splatting is a bonus
IT-Kenntnisse:
* Confident use of Microsoft Office, Git, and Linux (Ubuntu)
* In-depth knowledge of Python, C, or C++
* Proven experience with popular machine learning frameworks
Sprachkenntnisse :
* English (fluent spoken and written)
* German is an advantage
Soft Skills:
* High level of initiative
* Strong analytical skills
* Structured and independent way of working
* Ability to work in a team
* Goal-oriented