The Department of Urology offers an exciting position for a PhD student within the EU-funded Marie Skłodowska-Curie Innovative Training Network
CLARIFY (CLoud ARtificial Intelligence For pathologY). CLARIFY is an innovative, multinational, multi-sectorial, and multidisciplinary research and training program that links two highly differentiated specialties: engineering and medicine, with a focus on digital pathology. Our department is one of the nine host institutions.
Your research project:
As Early Stage Researcher 10 (ESR10), you will carry out the project entitled "Improving high-risk non-muscle invasive bladder cancer diagnosis and prognosis by digital pathology". The research objectives are to improve diagnosis and prediction of response to treatment (BCG) in high-risk non-muscle invasive bladder cancer (HR-NMIBC) patients by studying the histopathological patterns of HR-NMIBC by image analysis together with clinicopathological biomarkers. You will:
- Generate an annotated database of HR‐NMBC patients including BCG-responders and BCG non-responders in order to improve, by artificial intelligence, precision and reproducibility of this classification.
- Define the requirements of an image analysis system which permits an effective classification of BCG‐responders and BCG non-responders.
- Analyze the clinical significance of the new morphological patterns automatically identified by deep learning algorithms which are differentially present among both patient subgroups.
Your fellow ESRs 1-9 mainly focus on development and implementation of deep learning networks based on extraction of tumor histological features. These algorithms are then used for image analysis in specific bladder tumors by you (ESR10) and in breast (ESR11) and skin (ESR12) tumors to improve diagnosis and prognosis.
Secondments:You will have your main workplace at Erasmus MC, but mandatory secondments at different partner institutions are also required. Secondments are planned at the Stavanger University Hospital (Norway) in month 17-21 for WSI digitalization work flow and digital pathology diagnosis research training, at Tyris Software (Spain) in month 30‐31 for usability and validation of clinical applications research training, and at INCLIVA Biomedical Research Institute (Spain) in month 32‐33 for image‐based diagnosis of spitzoid melanocytic lesions research training.