We are offering two PhD positions for our MARBLE project.
We are offering a fully funded PhD position for research on detection and quantification cancer in 4D (contrast enhanced) MRI imaging. While population-based breast cancer screening with mammography has shown to be very effective, mammography alone is not sufficient for the adequate screening of women who are carriers of genetic mutations or have other risk factors for breast cancer. In this project, you will research how you use prior imaging and associated clinical information to improve the detection and classification of cancer using deep learning in these high-dimensional images. In particular, as prior information in the form of mammography, digital breast tomosynthesis or MRI is often available you will investigate how to use this information to improve the performance of the detection and classification systems. A part of the project will be devoted on researching unsupervised methods to ensure stability of these models to different acquisition and machine parameters. You will work in close cooperation with a clinical PhD student to determine the optimal moment of cancer detection, the value of the developed methods for earlier cancer detection and the consequences of later detection on prognosis. In this project you will work closely with our industrial partner Screenpoint Medical, the Data Science group at the Radboud University and the clinicians involved. You will have large datasets with expert annotations to your disposal. There is a team of scientific programmers which supports our deep learning research and we have a large cluster of computers equipped with high-end GPUs for large scale experimentation.
Specific requirements: Programming and expertise in deep learning model development are essential.
We are offering a fully funded PhD position on the evaluation of breast cancer screening with DBT and MRI and the impact of automated analysis on this process. Early detection of breast cancer enables timely treatment and is the key technique for the improvement of breast cancer specific survival. In a large retrospective database you will evaluate the frequency of non-detection of breast cancers, and the potential impact of this on cancer stage and outcome. You will work in close cooperation with a technical PhD student, who will develop automated tools for image evaluation (mainly MRI) and cancer detection. A large part of the research will consist of the clinical evaluation of the automated tools developed in house and by our industrial partner ScreenPoint Medical (focussing on DBT), with the aim of enhancing early detection and improving lesion classification. You will evaluate how these tools can best be used in clinical practice and to what extent they improve the performance of radiologists with different level of experience. In addition you will investigate potential risk predictors in the images to improve stratification of the screening population.
Specific requirements: Statistics, R/SPSS, knowledge of medical imaging
For this project the Diagnostic Image Analysis Group of the Radboud University Medical Center, Nijmegen (The Netherlands), is seeking a two PhD students. This is an excellent opportunity to develop and implement cutting-edge technology to have an impact on breast cancer research and personalized cancer treatment.
You should be a creative and enthusiastic researcher with a MSc in a relevant field, depending on the position such as medicine, technical medicine, medical image analysis, computer vision, or machine learning. Good communication skills are essential.
Your performance will be evaluated after 1 year. If the evaluation is positive, the contract will be extended by 3 years. 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.
Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy.
Read more about what it means to work at Radboudumc and how you can do your part.
The vacancy will soon be open for applications. Further information can be obtained from Dr. Jonas Teuwen, assistant professor or Dr. Ritse Mann, breast radiologist. Applications will be reviewed on an ongoing basis until the position is filled.
Recruitment agencies are asked not to respond to this job posting.