Internship /Praktikum – Computer Vision, Machine Learning & Medical Navigation – 6 months | Start Spring 2027 (6 Monate)

Work Flexibility: Not available Your Mission Are you passionate about artificial intelligence and medical technology? During this internship, you will help develop Computer Vision and Machine Learning solutions for next-generation medical navigation technologies. You will work with real-world image and sensor data, contribute to innovative development projects, and collaborate with experienced engineers in an international MedTech environment. This opportunity allows you to strengthen your technical expertise, gain practical experience with advanced AI technologies, and contribute to innovations that support future computer-assisted and robot-assisted surgical procedures.

What You'll Do

Develop and evaluate prototypes and algorithms using Computer Vision and Machine Learning methods. Analyze image and sensor data to improve the performance of medical navigation solutions. Apply Deep Learning, OpenCV, and related technologies to technical challenges. Support research and development activities for innovative medical technology applications. Collaborate with multidisciplinary engineering teams to deliver impactful project outcomes. What You'll Bring Currently pursuing a Master's degree in Electrical Engineering, Computer Science, Physics, Medical Engineering, Microsystems Engineering, or a related field. Initial experience with Python programming. Basic knowledge of Computer Vision, Machine Learning, or image analysis techniques. Initial exposure to OpenCV, PyTorch, or comparable development frameworks. Very good English skills (B2) or higher. ​ What's In It for You Paid six-month full-time internship (voluntary internship alongside studies, mandatory internship, or a combination of both possible) Start date: March or April 2027 Location: Freiburg (Breisgau, Germany) Flexible working hours and attractive holiday allowance Mentoring and training to support your growth Hands-on projects with real-world impact in an international environment ​ Applic