Research Scientist with focus on Interventional Ultrasound (f/m/x) at ImFusion GmbH (München, Deutschland)
Your mission
- Develop medical imaging algorithms with a focus on real-time 3D ultrasound
- Perform multi-modal image segmentation and trajectory estimation with Deep Learning approaches that you develop
- Contribute to the productization of our interventional imaging framework
- Manage projects in close collaboration with our industry customers
- Publish results and represent our company at conferences
Your profile
- M.Sc. in Computer Science or a related field and 3+ years of industry experience, PhD is a plus
- Applied knowledge of Deep Learning frameworks such as PyTorch or Tensorflow for image segmentation
- Strong programming skills in C++, Python is a plus
- Experience in 3D ultrasound, e.g. 3D reconstruction / compounding, multi-modal registration, etc. is a plus
- Reliable Team player and quick learner
- Proficient in English
Why us?
- Contribute to creative and exciting projects with renowned customers around the world
- See your work integrated in actual medical products that improve patients’ lives
- Be part of an international, dynamic and highly skilled team where you can both make an impact and continue to learn
- Stay connected with the academic community, write scientific papers and attend conferences
- Enjoy the agility of a start up paired with the safety of a grown company
- Benefit from flexible working hours and an option for home office
- Earn a competitive salary based on your experience
ImFusion is a growing company located in Munich, conducting research, development and consulting in advanced medical image computing technologies and computer vision. Our customers include small and large medical device companies as well as academic research labs. We wish to expand our team with talented and motivated people. You think you can be a good fit? We'd love to hear from you! We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status.
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