Data-Efficient CV Internship for Real-World Impact

TNO; Delft; On-site; EUR 6,200 - 7,500; Full time

Benefits offered by this job

Internship stipend €615

Travel expense support

Jong TNO membership

Leave allowance 8h/mo

Job summary

TNO offers an internship focused on data-efficient computer vision with impact on infrastructure data collection and societal applications. You will explore self-supervised learning, few-shot learning, vision-language models, and foundation models, shaping a concrete research question with your supervisor.

Three options are available: predictive maintenance from drone imagery, asset extraction from street-view imagery, and video understanding for process monitoring.

Qualifications

• Background in Artificial Intelligence, Computer Science, Data Science, Robotics or related field.
• Experience with Python and machine learning frameworks.
• Interest in representation learning, foundation models, video understanding or CV research.

Responsibilities

• Develop data-efficient computer vision methods for limited annotated data.
• Experiment with self-supervised learning, few-shot learning and foundation models and evaluate results.
• Translate findings into prototypes and research reports and contribute ideas within the team.

Skills

Python

Machine learning

Computer vision

Tools

PyTorch

TensorFlow

Job description

TNO offers an internship focused on data-efficient computer vision with impact on infrastructure data collection and societal applications. You will explore self-supervised learning, few-shot learning, vision-language models, and foundation models, shaping a concrete research question with your supervisor.

Three options are available: predictive maintenance from drone imagery, asset extraction from street-view imagery, and video understanding for process monitoring.