In this Masters thesis you will work with Vision-Language-Action (VLA) models which enable robots to understand a scene follow natural-language instructions and execute reliable interpretable actions in the environment.
- As part of your work you will explore recent VLA methods and define evaluation criteria for accuracy robustness and data efficiency.
- You will be responsible for the implementation and benchmarking of strong baselines for manipulation tasks.
- Another key activity in your work is building the necessary data pipeline for training and evaluation.
- Finally you will develop prototypes for action decoding strategies.
Qualifications :
- Education: master studies in the field of Computer Science Robotics Electrical Engineering Mechanical Engineering or comparable with good grades
- Experience and Knowledge: experienced in Python and PyTorch; background in computer vision LLMs / language modeling imitation or reinforcement learning or multimodal learning; good software engineering practices (Git Clean code reproducible experiments documentation); famialirity with distributed training frameworks ROS/ROS2 basic robot kinematics/control simulators (e.g. Isaac MuJoCo) data processing at scale and experiment tracking (e.g. Weights & Biases) is a bonus
- Personality and Working Practice: you have a curious and proactive personality coupled with a structured work approach makes you comfortable driving your own experiments and effectively communicating results
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Babu Harisankar (Functional Department)
49 152
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
In this Masters thesis you will work with Vision-Language-Action (VLA) models which enable robots to understand a scene follow natural-language instructions and execute reliable interpretable actions in the environment.As part of your work you will explore recent VLA methods and define evaluation cr...
In this Masters thesis you will work with Vision-Language-Action (VLA) models which enable robots to understand a scene follow natural-language instructions and execute reliable interpretable actions in the environment.
- As part of your work you will explore recent VLA methods and define evaluation criteria for accuracy robustness and data efficiency.
- You will be responsible for the implementation and benchmarking of strong baselines for manipulation tasks.
- Another key activity in your work is building the necessary data pipeline for training and evaluation.
- Finally you will develop prototypes for action decoding strategies.
Qualifications :
- Education: master studies in the field of Computer Science Robotics Electrical Engineering Mechanical Engineering or comparable with good grades
- Experience and Knowledge: experienced in Python and PyTorch; background in computer vision LLMs / language modeling imitation or reinforcement learning or multimodal learning; good software engineering practices (Git Clean code reproducible experiments documentation); famialirity with distributed training frameworks ROS/ROS2 basic robot kinematics/control simulators (e.g. Isaac MuJoCo) data processing at scale and experiment tracking (e.g. Weights & Biases) is a bonus
- Personality and Working Practice: you have a curious and proactive personality coupled with a structured work approach makes you comfortable driving your own experiments and effectively communicating results
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Babu Harisankar (Functional Department)
49 152
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
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