At sewts we automate what others can’t. Gripping of deformable materials like textiles is a task most humans see as intuitive and simple. However, this is a complicated task for robots as they lack the detailed and contextual understanding of where and with what level of sensitivity to handle these textiles. As deep-tech enthusiasts, we teach robots human-like perception skills.
 
We are building a foundational technology stack called sewts.JUPITER. JUPITER uses genAI to simulate realistically the behavior of deformable & soft objects to create corresponding computer vision models and grabbing strategies. Based on our physical AI first time ever robots get enabled to handle soft & deformable materials. With over €10M in funding we will bring automation into all untapped industries, like cloth manufacturing, textiles handling, recycling & e-commerce.

We are looking for a hands-on, reliable 'Student Assistant' to support our AI data collection process focused on workwear classification and soiled item sorting. This role is essential in helping us train cutting-edge machine learning models by ensuring accurate, high-quality data capture.

This is how you will support us:

• Place workwear items on the conveyor system according to provided instructions. 

• Ensure items are positioned correctly for the data collection system to capture accurate information.

• Monitor the process and report any issues with item flow or system behavior.

• Handle garments carefully and keep the work area organized.