Vacancy: Deep learning for improved prognostics in prostate cancer

The Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center, Nijmegen, is offering a PhD position.

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Background

Most men die with, not because of prostate cancer. Current population models to assess which patients benefit from therapy are no longer adequate in the age of personalized medicine. The Dutch Cancer Society has awarded us a grant to investigate whether it is possible to use two new technologies: digital pathology and deep learning to obtain patient specific biomarkers to improve the assessment of prostate cancer prognosis. Within this project we will develop deep learning networks to extract known and identify novel biomarkers from digitized tissue specimens from a retrospective cohort of prostate cancer patients. These biomarkers will be integrated into improved prostate cancer risk models and validated in a multi-center prospective trial.

You will be working at the intersection of machine learning and medicine, co-developing the deep learning models and validating them in clinical practice. You will be actively involved in managing the clinical trial and communicating with our partners. The end result of your project will thus have a high chance of directly impacting clinical care and cancer research.

Requirements

You should be a creative and enthusiastic researcher with an MSc degree in (Technical) Medicine, Biomedical Engineering, Biomedical Sciences, Computer Science or similar, with an affinity with medical topics and an interest in machine learning/image analysis. Experience with clinical trials, programming (Python or C++), or deep learning are considered a pre. Good communication skills and affinity with computers are essential.

Terms of employment

You will be appointed as a PhD student with the standard salary and secondary conditions for PhD students in the Netherlands. Your performance will be evaluated after 1 year. If the evaluation is positive, the contract will be extended by 3 years. The research should result in a PhD thesis.

Organization

The Diagnostic Image Analysis Group (DIAG) is a research division of the Department of Radiology and Nuclear Medicine of the Radboud University Medical Center in Nijmegen. Nijmegen is the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboud UMC is a leading academic center for medical science, education and health care with over 8,500 staff and 3,000 students.

The focus of the Diagnostic Image Analysis group is the development and validation of novel methods in a broad range of medical imaging applications. Research topics include image analysis, image segmentation, machine learning, and the design of decision support systems. Application areas include breast imaging, prostate imaging, digital pathology, lung imaging, and retinal imaging. Key to the success of the group is close cooperation with clinicians. Currently the group consists of around 40 researchers.

Application

Please apply by following this link. Only if this does not work, you can send applications as a single pdf file to geert.litjens@radboudumc.nl. In this pdf file the following should be included: CV, list of followed courses and grades, letter of motivation, and preferably a reprint of your Master thesis or any publications in English you have written. This application will remain open until the position has been filled. Applications are processed immediately upon receipt.

More information

For more information please contact Geert Litjens by e-mail.