Internship - Machine Learning for Computer Vision (f/m/x)
Internship - Machine Learning for Computer Vision (f/m/x)
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
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 projects 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 Masters 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 SafradinRequired Experience:
Intern
Employment Type
Full-Time
