Internship - Machine Learning for Computer Vision (f/m/x)
Eggenstein-Leopoldshafen, Germany
ZEISS Group
ZEISS is an international leading technology enterprise operating in the optics and optoelectronics industries.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 offerDirect 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
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
Your ZEISS Recruiting Team:
Franziska GansloserTags: Classification Computer Science Computer Vision Data analysis Machine Learning Mathematics Physics Python Research
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