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 Your Role 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 Your Profile 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 Sounds exciting? Then become part of teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records etc.). Your ZEISS Recruiting Team: Selina Safradin