Intern AI Innovation for Medical Devices (f/m/x)

ZEISS Group

Oberkochen

On-site

EUR 8,900 - 13,000

Part time

14 days+

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Job summary

ZEISS Group in Germany is seeking a tech-enthusiastic student to join the AI & Digital Twin group of Advanced Development at ZEISS Meditec for proof-of-principle demonstrators in next-gen healthcare features.

As part of the internship, you will work on AI and digital twin features, design computer vision solutions for advanced biomedical visualisations, and collaborate with product management and clinical partners in an interdisciplinary team.

Qualifications

  • Enrolled in a bachelor or master program in computer science, electrical engineering, computer engineering, biomedical engineering or similar.
  • Prior experience with AI/ML or computer vision methods and frameworks, preferably for medical image processing.
  • Proficient in one or more general purpose coding languages, preferably Python.
  • Familiarity with optimization, scientific visualization libraries and graphic user interfaces is a plus.
  • Thrilled to translate technology skills into algorithms and demonstrators for real surgical needs.
  • Creative, innovative, motivated and well-organized.
  • A good communicator, both in German and English.

Responsibilities

  • Work on potential AI and/or digital twin features for future medical devices
  • Design solutions for computer vision problems towards advanced biomedical visualisations
  • Evaluate and refine your approach on real-world data
  • Build proof-of-principle demonstrators & test with product management and clinical partners
  • Work closely in an interdisciplinary team of AI & Digital Twin experts and application experts
  • Participate in lively student community at ZEISS

Skills

AI/ML
Computer Vision
Python

Education

Bachelor/Master student in CS/EE/biomedical eng

Job description

Seeing beyond - future of medical technology

For more than 100 years, ZEISS medical technology has been driving progress in ophthalmology and microsurgery. In ophthalmology, our solutions help to maintain and improve people’s vision at every stage of their lives. In microsurgery, our solutions enable targeted interventions on diseased tissue so that small and sensitive organs continue to function optimally.

Medical technology from ZEISS supports medical professionals in improving the lives of patients worldwide. The fact that our actions have a direct impact on people’s well-being is what drives us every day.

Your Role

We seek a tech-enthusiastic student to join the AI & Digital Twin group of Advanced Development at ZEISS Meditec to help us shaping proof-of-principle demonstrators for next-gen healthcare product features. As member of our team, you will leverage your AI, digital twin & computer vision skills and passion to tackle open real-world challenges.

During your internship, you will:

  • Work on potential AI and/or digital twin features for future medical devices
  • Design solutions for computer vision problems towards advanced biomedical visualisations
  • Evaluate and refine your approach on real-world data
  • Build proof-of-principle demonstrators & test your solution with product management and our clinical partners
  • Work closely in an interdisciplinary team of AI & Digital Twin experts and application experts
  • Participate in lively student community at ZEISS
Your Profile
  • Enrolled in a bachelor/ master program in computer science, electrical engineering, computer engineering, biomedical engineering or similar
  • Prior experience with AI/ML or computer vision methods and frameworks, preferably for medical image processing
  • Proficient in one or more general purpose coding languages, preferably Python
  • Familiarity with optimization, scientific visualization libraries and graphic user interfaces is a plus
  • Thrilled to translate your technology skills and curiosity into algorithms and proof of principle demonstrators to solve real surgical needs
  • Creative, innovative, motivated and well-organized
  • A good communicator, both in German and English
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