Internship/ Master Thesis- Foundation Models for Detection of Unknowns in Visual Perception (m/f/d)
At CARIAD, we're bundling and further expanding the Volkswagen Group's software expertise. We’re uniting over 6,500 global experts to build a scalable technology stack, including a software platform, unified electronic architecture and reliable connection to the automotive cloud.
Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.
Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.
It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey!
YOUR TEAM
Our "Visual Perception" team is looking for "intern / working student / thesis" to support us. We are a small team of 6 employees, with the focus on innovation technologies and getting the innovation realized by prototype setups e.g. in a vehicle.
The team is working in with an agile project setup with the spirit to "get things done".
Even we are a small team, we are at 3 locations and therefore established a good way of working remote and align in virtual meetings, For sure to get the prototype up and and running we meet and work in the garage.
WHAT YOU WILL DO
- Collaborate and support our PhD students on a variety of projects within the field of Visual Perception
- Analyse and present research literature related to your research project
- Implement and extend promising approaches in our software environment
- Develop algorithmic ideas addressing open research challenges related to the topic "foundation models / generative models for detecting unknowns in visual perception"
- Conduct, document and design comprehensive experiments on internal as well as public datasets
WHO YOU ARE
- Enrolled student in computer science, data science, robotics or equivalent field
- Structured and independent work, above-average commitment and flexibility
- Profound knowledge in machine learning, especially deep neural networks
- Proficiency in Python and deep learning frameworks (PyTorch, OpenCV, scikit-learn)
- Analytical understanding of complex systems and problem-solving skills
- Fluent in English
- Experience in object detection, semantic segmentation and / or foundation models in computer vision would be beneficial
NICE TO KNOW
- Remote work options
- Internship
- Duration : 3 to 6+ months
- 35-hour week
- Working Student
- Duration : 6 months
- 20 h / week, up to 35 h / week during semester break
- If you have further questions about the candidate journey at CARIAD, please contact us :
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