Assistant Doctorant - 0131

About the job

Recherche

PhD position in computational pathology and shole slide image analysis

The Institute of Pathology, at the Lausanne University Hospital (CHUV) is opening a PhD Position for a start date on April 1st 2026:

Contexte

The Lausanne University Hospital (CHUV) is one of five Swiss university hospitals. Through its collaboration with the Faculty of Biology and Medicine of the University of Lausanne and EPFL, CHUV plays a leading role in the areas of medical care, medical research, and training.

We are inviting applications for a fully funded PhD position focused on computational pathology, with a specific emphasis on the analysis of whole-slide images (WSIs) to distinguish between multiple primary lung tumors and metastatic disease. The successful candidate will join a dynamic interdisciplinary team working at the intersection of pathology, computational science, and machine learning.

This research will contribute to improving diagnostic accuracy in thoracic oncology by developing novel image‑based computational methods to support decision‑making in challenging clinical scenarios where multiple lung lesions are present. The project will leverage digital histopathology images and associated clinical metadata to build robust, interpretable algorithms for tumor classification, comparison, and characterization.

The PhD student will be co‑mentored by faculty with expertise in pathology, machine learning, and biomedical image analysis, and will have the opportunity to contribute to high‑impact publications and translational research.

Mission

Develop image analysis algorithms to differentiate multiple primary lung tumors from intrapulmonary metastases using WSIs

• Design computational experiments to validate and benchmark algorithms on expert‑annotated datasets
• Contribute to the development of interpretable tools that integrate into clinical workflows and support precision diagnostics

Key Responsibilities

WSI Preprocessing & Annotation

• Preprocess large histopathology datasets (e.g., stain normalization, tiling, artifact removal)
• Collaborate with pathologists for region annotation and ground‑truth labeling

Algorithm Development

• Design and implement machine learning pipelines (e.g., CNNs, graph‑based models, patch‑level feature extractors) for tumor differentiation
• Develop similarity metrics or learned embeddings for comparing tumors across slides or within patients

Experimental Design & Validation

• Conduct rigorous experiments to assess diagnostic accuracy, reproducibility, and generalizability of models
• Analyze results statistically and in collaboration with clinical experts

Scientific Communication

• Contribute to the writing of scientific manuscripts, conference presentations, and progress reports
• Participate in interdisciplinary research meetings and collaborative planning sessions

Tool Support & Collaboration

• Develop modular, well‑documented code and interfaces to facilitate use by other researchers or collaborators
• Mentor undergraduate students or junior lab members on aspects of data preparation and model development

Professional Growth

• Stay current with state‑of‑the‑art literature in computational pathology, deep learning, and lung cancer diagnostics
• Attend scientific conferences and training workshops

Profil

• Master’s degree in Computer Science, Biomedical Engineering, Electrical Engineering, Applied Mathematics, or a related field
• Strong programming proficiency in Python and experience with scientific computing libraries (e.g., NumPy, SciPy, scikit-image)
• Experience working with digital histopathology data or other large-scale imaging datasets
• Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow)
• Prior work involving classification, segmentation, or similarity analysis in medical imaging or histology
• Experience with whole slide image handling libraries (e.g., OpenSlide, SlideIO)
• Understanding of histopathological features relevant to lung cancer (e.g., tumor architecture, cell morphology)
• Excellent communication skills and the ability to work in a collaborative, multidisciplinary setting.

Nous offrons

To become an employee of the world-famous University Hospital Center from the Canton of Vaud is an assurance of:

• First-rate social benefits such as a Paternity Leave of 20 days and a Maternity Leave of 4 months (there is also the possibility to obtain a complementary breastfeeding leave of 1 month) ;
• Regular salary progression adapted to your responsibilities ;
• A right to at least three days of training per year, by accessing a wide offer of courses not only from the CHUV Training Center but also from external providers ;
• Possibility to access one of the 500 furnished apartments offered in the surrounding neighborhoods in case of relocation in Switzerland ;
• Discounts proposed on social and cultural events, goodies and other services, thanks to the “H-Oxygène” association ;
• Signing up to our Mobility Plan and benefit from different advantages (discounts on public transportation, promotion of “Mobility” car fleet and discounts on electric bikes) ;
• Being able to enjoy our high-quality corporate restaurants, located in every hospital building, with employees’ discount.

Contact et envoi de candidature

Contact person in case of questions about this role : Prof. Sabina Berezowska, au 021 314 72 11.

All of our applications are processed electronically. For this reason, we kindly ask you to apply exclusively by clicking on the APPLY button at the bottom of the advertisement.

Should you experience any problems with your application, you can consult our document "how to apply online". In case of technical issues, you can contact our Recruitment team who will help you (E-Mail schreiben / +41 21 314 85 70)

The CHUV applies the highest quality requirements as part of its recruitment process. In addition, mindful to promote workplace diversity and inclusion we strive to ensure equal treatment and avoid any discrimination. We are looking forward to receiving your application.

We would like to inform external recruitment agencies that any application inserted directly on our recruitment platform won’t be accepted and cannot be charged. Thank you for your understanding.