Hi there! 🙂
Are you enrolled in Computer Science, Robotics or a similar field, are looking for a master thesis or internship, and are enthusiastic about Computer Vision or Robotics? Then we might have something for you! 🙂
At Sevensense we push the frontiers of mobile robotics. Our mission is to build the eyes and brain for the robots of the future! Equipped with our technology, mobile machines can autonomously navigate in dynamic and crowded environments, such as airports, supermarkets, warehouses and train stations. And we’re always looking for intellectually curious and highly motivated students to collaborate with!
This “job offer” is meant for spontaneous applications from students seeking opportunities for master theses or internships. These opportunities can open any time - thus please don’t hesitate and contact us via this form and we’ll see whether we have a project open that aligns well with your interests and skills. We’re always seeking for great minds with great passion!
We usually offer master theses & internships in the fields of:
The ideal candidate should demonstrate teamwork, proactivity, autonomy and have a strong desire for solving exciting and challenging problems. In general, good knowledge in some coding language (C++, Python, Rust - depending on the project) is a must. Hands-on (coding) experience in the field of your interests is a big plus. For internships we prefer students towards the end of their master program.
When collaborating with us, you’ll join a young and agile company which is now part of ABB. You’ll join us in our office in the heart of Zürich, featuring an endless supply of coffee, chocolate and snacks.
If you are enthusiastic about bringing Sevensense to the next level, curious about the opportunity and want to be part of our fast-growing team, apply via our platform now. Please reach out to us if you have questions or feel unsure about some requirements.
At Sevensense we value diversity and all the features that make us all unique. We encourage everyone to apply, regardless of their gender, personal or social background.