Beschreibung

Master Thesis on Generative AI for Biomedical Imaging

Robert-Bosch-Campus 1, 71272 Renningen, Germany

Full-time

Robert Bosch GmbH

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application

Job Description

• Biomedical imaging provides great potential for diagnostics and research. However, many AI applications are hampered by the lack of application-specific data. Foundation models promise to solve the issue by pre-training on large amounts of data in a self-supervised manner. In this thesis you will explore how these ideas can be applied to the analysis of fluorescence microscopy images.
• During your Master thesis, you will conduct a literature review on the intersection of AI and biomedical imaging.
• You will design and implement a multimodal text-image model and evaluate the implementation of the model.
• Furthermore, you will work with large image datasets.
• Last but not least, you will be contributing to a meaningful field of research.

Qualifications

• Education: Bachelor studies in the field of Machine Learning, Bioinformatics or comparable
• Experience and Knowledge: in Python and programming projects; experience in designing and implementing machine learning models; knowledge of computer vision fundamentals an advantage
• Personality and Working Practice: motivated and independent
• Languages: good in German and English

Additional Information

Start: according to prior agreement
Duration: 9 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
Jan Rudolph (Functional Department)

Christian Grumaz (Functional Department)

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