Do you want to contribute to the world’s first prospectively evaluated algorithm-supported workflow for digital pathology, which will increase the time of pathologists for complex diagnostics and reduce the wait time for patients?
Due to the tripling of skin cancer incidence over the past two decades, more skin biopsies and resections are performed than ever before. This has led to an enormous increase in workload for pathologists, who perform the microscopic diagnostics of skin samples. Machine learning and specifically deep learning offers a path to automating the diagnoses of skin samples, which would reduce the pressure on pathologists and the cost of diagnosis, both in time and money.
We are looking for a Ph.D. candidate who is not just interested in developing an algorithm which can perform skin diagnostics at the level of an expert pathologist, but also explicitly wants to identify the most fruitful way of integrating these algorithms into the routine workflow.
The Ph.D. candidate will develop algorithms for the segmentation of different skin tissue classes, subtyping of basal cell carcinoma, and identification of rare incidental findings. Subsequently, the candidate will focus on the development and prospective evaluation of the optimal algorithm-integrated workflow in a real-world clinical setting. After completion, this will result in the world’s first prospectively evaluated algorithm-supported workflow for digital pathology, which will increase the time of pathologists for complex diagnostics and reduce the wait time for patients.
The research should result in a Ph.D. thesis.
Tasks and responsibilities
Within this project you will:
Develop and validate deep learning algorithms to identify varying types of histopathologic skin diseases such as basal cell carcinoma.
Identify the best strategies to use such algorithms in clinical practice in close collaboration with our pathologists.
Implement this strategy in clinical workflow with the aid of our industrial partner
Evaluate the use of the algorithm in real-world clinical practice.
You are a creative and ambitious researcher with an MSc degree in Computer Science, Data Science, Engineering, Technical Medicine, Biomedical Sciences or similar, with a clear interest in artificial intelligence and medical image analysis. Good communication and organizational skills are essential. Experience with deep learning and programming, preferably in Python, are a plus and should be evident from the (online) courses you've followed, your publications, GitHub account, etc.
The Computational Pathology Group (CPG) is a research group of the Department of Pathology of the Radboud University Medical Center. CPG works closely together with the Diagnostic Image Analysis Group (DIAG) of the Department of Radiology and Nuclear Medicine. We develop, validate and deploy novel medical image analysis methods, usually based on machine learning technology and focusing on CAD. Application areas include diagnostics and prognostics of breast, prostate and colon cancer. Our group is among the international front runners in the field, witnessed for instance by the highly successful CAMELYON16 and CAMELYON17 grand challenges which we organized. We closely collaborate with clinicians and industry.
Working at Radboudumc
Radboudumc aims to be at the forefront of the development of innovative, sustainable and affordable healthcare. Our mission is 'to have a significant impact on healthcare'. We believe we can achieve that by providing excellent quality, participatory and personalized healthcare, operational excellence and by working together in sustainable networks. The starting point for this is patients and their quality of life. Throughout all this, patient care, research, and education go hand in hand. To realize our mission, we are searching for colleagues who want to take on this challenge with us; employees who are excellent in their field of expertise and give it their all by pushing boundaries and providing 'that little bit more'. At Radboudumc, you gain confidence, receive and take responsibility to successfully make these changes. For the best patient care and the best future of healthcare.
Starting date is March 1, 2020.
Upon commencement of employment, we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be, depending on the type of job, a screening based on the provided cv. Radboud university medical center’s HR Department will apply for this certificate on your behalf.
Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.
Please send a motivation letter with your CV to express your interest in this position. Add a list of followed courses and grades and preferably a reprint of publications in English you have written.