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The PhD research will entail an international recurrence case study focusing on applying and optimizing 3D X-ray virtual histology methods by micro-CT for recurring thyroid tumors. The acquired and existing database will be used to further develop ML models for the automated detection of clinically relevant markers. The goal is to develop the technique towards potential clinical use to enable precision medicine diagnostics for the patient and couple it with high-field MRI imaging to extend towards in-vivo applications. The project is interdisciplinary, and the PhD student will work in close collaboration with researchers and clinical experts from the University of Bern.
Your contribution:
1. Application and further development of 3D virtual histopathology by X-ray phase contrast micro-CT for recurring thyroid carcinoma cases using FFPE blocks.
2. Further development of ML tools and models for the automated detection of clinically relevant morphological features for the diagnostics of such tumors.
3. Establishment of a unique 3D micro-CT histology database for recurrent thyroid carcinomas.
4. Data management and data treatment.
5. Extension and coupling with high-field MRI technology towards in-vivo diagnostics.
Your profile:
You would like to make a major impact on personalized medicine of thyroid carcinomas, 3D cancer diagnostics, and revolutionize digital pathology. You are highly motivated, communicative, and passionate about working in an interdisciplinary field and fulfill the following criteria:
* Completed Master's degree in biomedical engineering, physics or similar.
* Strong hands-on lab skills.
* Some experience with X-ray methods and imaging.
* Preferably some additional experience in the biomedical domain and/or in image processing.
* Preferably some experience using ML models and tools (e.g. radiomics) in image processing and programming (Python, C, Matlab, etc.).
* Fluent in English; German is beneficial.
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