Internship/Master Thesis in deep learning-based methods for microscopy in Oberkochen bei ZEISS Group

ZEISS Group

Your Role

We seek a motivated and talented intern or Master's thesis student to work on a research project focused on exploring the potential of deep learning-based methods for microscopy. The successful candidate will have the opportunity to implement and evaluate DL-based methods and collaborate with a team of experts in the field. This is a unique chance to gain hands-on experience in cutting-edge research and contribute to the development of advanced microscopy techniques. Your role:

Familiarize yourself with state-of-the-art deep learning-based methods for microscopy
Implement DL-based and analytical methods for microscopy
Evaluate methods with benchmark datasets
Possibly conduct real-data validation
Collaborate with the team to achieve project goals and deliverables
Communicate project progress and results to mentors and team members
Document the study results

Your Profile

Master's degree student in computer science, bio-engineering or related fields
Strong background in machine learning or related fields
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch)
Experience with image processing (OpenCV, Open3D)
Familiarity with microscopy is a plus
Excellent problem-solving skills
Detail-oriented and able to work in a team
Self-motivated and independent working style with a passion for exploring complex and innovative topics
Good written and oral communication skills in English
Motivated, curious, and eager to learn
Available to work for at least six months (internship or Master's thesis)