Step out of your comfort zone, excel and redefine the limits of what is possible. That's just what our employees are doing every single day – in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people.

In a spacious modern setting full of opportunities for further development, ZEISS employees work in a place where expert knowledge and team spirit reign supreme. All of this is supported by a special ownership structure and the long-term goal of the Carl Zeiss Foundation: to bring science and society into the future together.

Join us today. Inspire people tomorrow.

Diversity is a part of ZEISS. We look forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, philosophy of life, disability, age, sexual orientation or identity.

Apply now! It takes less than 10 minutes.

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Motivation of the work

Engage in pioneering research aimed at classifying and quantifying medical waste through advanced machine learning techniques. This project not only seeks to enhance the understanding of medical waste management but also aims to contribute to recycling opportunities and inform regulatory decisions.

We offer

• Direct mentorship from experienced professionals in the field

• Interaction with a dynamic and interdisciplinary team

• Access to a vibrant student community for networking and support

• Opportunity to contribute to a public-funded project with real-world impact

• Work on the classification of x-ray images using machine learning algorithms

• Gain experience with Python (or other relevant programming languages) for machine learning tasks

• Develop transferable technical skills in machine learning and data analysis

• Be challenged to creatively solve problems and contribute to the project's objectives

• Develop algorithms that could enable recycling opportunities and influence regulatory decisions

• Experience the intersection of technology, healthcare, and environmental sustainability

Profil

• You are enrolled in a master's program in computer science, mathematics, physics, or a related field, and have excellent academic results (please include transcripts with your application)

• Demonstrated experience in machine learning and computer vision (through coursework, projects, or internships)

• Proficiency in Python (or similar languages established for machine learning)

• Strong analytical, problem-solving, and communication skills (in English and/or German)

• A passion for innovation and a desire to apply theoretical knowledge to practical challenges

• High intrinsic motivation and the desire to work in interdisciplinary teams

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