Student Assistant – Medical Image Analysis (f/m/d)

ZIB; Berlin; Hybrid; EUR 6,700 - 7,800; Part time

Benefits offered by this job

Flexible working hours

Payment according to Berlin state min.

Combine position with Master’s thesis

International and inspiring work环境

Professional/personal development

Job summary

Zuse Institute Berlin (ZIB) seeks a Student Assistant - Medical Image Analysis (f/m/d) to advance an AI-assisted surgical planning project in orthopedics. The role runs 40 hours per month, limited until 30 September 2027, with on-site collaboration and hybrid options.

You will work in imaging, ML, and clinical applications, shaping state-of-the-art methods and contributing to research results and publications.

Qualifications

• Enrollment in Mathematics, Computer Science or a related field.
• Solid programming skills in Python.
• Experience with CUDA.
• Strong background in machine learning and computer vision.
• Familiarity with PyTorch is desirable.
• Experience with medical imaging is a plus.
• Research experience in a university or industry setting is a plus.
• Good communication and teamwork.

Responsibilities

• Develop end-to-end deep learning pipelines for medical image segmentation.
• Work on data preprocessing, training workflows, and validating model performance.
• Create data visualizations and analyses to communicate results.
• Contribute to scientific experiments and publications.
• Support AI-assisted surgical planning research.

Skills

Python

CUDA

Machine learning

Computer vision

PyTorch

Medical imaging

Research experience

Team collaboration

Education

Enrollment in Mathematics, Computer Science or a related field

Tools

PyTorch

CUDA

Job description

Position Details

Within the research group Computational Diagnosis and Therapy Planning of the department Visual and Data-Centric Computing, we are looking for a Student Assistant - Medical Image Analysis (f/m/d) for 40 hours per month, limited until September 30, 2027 to support us in our research project on AI-assisted surgical planning for orthopedic surgery.

Background & Context

The project is funded by the German Federal Ministry of Research, Technology and Space and brings together partners from research, clinical practice, and industry. The goal of the project is to develop methods for the 3D reconstruction of patient-specific anatomy from 2D X-ray images, enabling more accurate and efficient surgical planning.

Your Tasks

You will work in an interdisciplinary research environment at the intersection of medical imaging, machine learning, and clinical application, with the opportunity to contribute to state-of-the-art methods and help shape the future of AI-assisted surgery. Depending on your interests and skills, you will contribute to different aspects of the project, including the development of end-to-end deep learning pipelines for medical image segmentation and neural implicit representations. Your work may involve data preprocessing, implementing training workflows, and validating model performance. You will have the opportunity to bring in and implement your own ideas, contribute to scientific experiments, and make valuable contributions to research publications. In addition, you will create data visualizations and analyses to communicate results, track research progress, and support the development of our methods.

Your Profile

• Enrollment in Mathematics, Computer Science or a related field
• Solid programming skills in Python and experience with CUDA
• A good background in machine learning and computer vision
• Familiarity with modern deep learning frameworks such as PyTorch is highly desirable
• Experience with medical imaging is a plus, but not required
• First experience in a research environment, for example through a student project, thesis, or research assistant position, is a plus, but not required
• Good communication skills and the ability to work effectively in a collaborative and interdisciplinary team

If you do not meet every requirement yet, we still encourage you to apply. We value motivation, curiosity, and the willingness to learn, and we are happy to support you in developing the skills needed for the role.

What you can expect

• Flexible scheduling of working hours
• Payment according to the Berlin state minimum wage (currently €14.84/hour) + capital allowance
• Opportunity to combine the position with your Master's thesis or other academic work
• An international and inspiring work environment
• Plenty of opportunities for professional and personal development

The Zuse Institute Berlin is committed to diversity, equal opportunities, and a respectful and inclusive working environment. In order to increase the proportion of women in areas where they are underrepresented, we expressly encourage women to apply. Irrespective of this, we welcome applications from all qualified candidates regardless of age, disability, ethnic or social background, religion or belief, sexual orientation, or gender identity. Research thrives on collaboration - therefore, we value your willingness to work regularly on-site at ZIB. Hybrid working is possible; however, we do not offer fully remote positions.

Contact

For further information about the position, please refer to our website www.zib.de or contactStefan Zachow ([e-mail]) or Mirko Konstantin ([e-mail]).