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

Zuse-Institut Berlin

Berlin

Vor Ort

EUR 21.000 - 22.000

Teilzeit

Vor 10 Tagen

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Benefits dieser Stelle

Flexible scheduling
Minimum wage pay + capital allowance
Thesis compatibility
International environment
Development opportunities

Zusammenfassung

Zuse-Institut Berlin invites applications for a Student Assistant in Medical Image Analysis to support AI-driven orthopedic surgery planning. The role involves developing end-to-end deep learning pipelines for medical imaging, data preprocessing, training workflows, and result visualization within an interdisciplinary team.

Flexible hours within 40 hours/month, on-site in Berlin with hybrid possibilities, and the chance to align the work with a Master’s thesis.

Qualifikationen

  • Enrollment in Mathematics, Computer Science or a related field.
  • Strong Python programming skills and CUDA experience.
  • Background in ML and computer vision, PyTorch preferred.

Aufgaben

  • Develop end-to-end deep learning pipelines for medical image segmentation.
  • Preprocess data, train workflows, and validate model performance.
  • Create data visualizations and analytics to communicate results.
  • Collaborate with interdisciplinary team and contribute to publications.

Kenntnisse

Python
CUDA
Machine learning
Computer vision
PyTorch
Medical imaging

Ausbildung

Math/CS student

Tools

CUDA toolkit
PyTorch
Git

Jobbeschreibung

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. Please note that we can only consider complete applications. These must include your CV, certificates/transcripts (Abitur certificate and, where applicable, Bachelor's degree certificate), a current overview of your module grades, and a certificate of enrollment.

November 15, 2026

Our private policy statement regarding application data is available at www.zib.de/impressum. For further job offers please visit our website atwww.zib.de/jobadvertisement.

Contact

For further information about the position, please refer to our website www.zib.de or contactStefan Zachow (zachow@zib.de) or Mirko Konstantin (konstantin@zib.de).

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