Ongeveer 21 uur geleden - VU - Amsterdam
The Vrije Universiteit Amsterdam School of Business and Economics established the Hermine Weijland Fellowship in 2017 with the aim of attracting and promoting …
The goal of this project is to automatically extract reliable biomarkers from multimodal and longitudinal retinal images using deep learning that can predict AMD progression.
Age-related macular degeneration (AMD) remains the leading cause of blindness in the elderly, affecting more than 50 million Europeans. About 15% of affected patients progress to irreversible vision changes and, ultimately, blindness. Therapies to slow progression are becoming available, but clinicians are currently insecure to foresee who will progress and will need swift action to save sight.
The goal of this project is to automatically extract reliable biomarkers from multimodal and longitudinal retinal images using deep learning that can predict AMD progression. How to effectively combine heterogeneous 2D and 3D data from different projections with deep learning architecture is a research question that will be addressed in this project, as well as the analysis of temporal evolution or the use of semi-supervised approaches when complete annotations are not available for some of the modalities. The automatically extracted biomarkers will be combined with other biomarkers, such as genetic and environmental markers, into a prediction model that can assess the risk of progression to late AMD. This model will give clinicians the possibility to identify patients at high-risk of progression and to provide them active surveillance and personalized therapy to prevent blindness.
You will be part of a multidisciplinary team, consisting of machine learning and clinical researchers and will work closely with the Ophthalmology departments in Radboudumc and ErasmusMC, as well as international groups and consortia.
We are looking for ambitious deep learning engineers, data scientists, or machine learning experts. You should be a creative, and enthusiastic and have an MSc/Ph.D. degree in Computer Science, Data Science, Physics, Engineering or Biomedical Sciences or similar, with a clear interest in deep learning, image analysis and medical applications. Good communication skills and expertise in software development, preferably in Python/C++, are essential. Experience with machine learning should be evident from the (online) courses you've followed, your publications, GitHub account, etc. Experience with medical image processing is preferred and you recognise yourself in the Radboud way of working.
Terms of employment
The PhD positions are for four years and have the standard salary and secondary conditions for PhD candidates in the Netherlands. The research should result in a PhD thesis. See also our page with general information about doing a PhD in our group. Read more about the Radboudumc employment conditions.
Additional information about the vacancy can be obtained from Dr. Clarisa Sánchez, associate professor. Use the Apply button to submit your application.
Upon commencement of employment we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be a screening based on the provided CV. Radboud university medical center’s HR Department will apply for this certificate on your behalf.
This vacancy is open until filled.
Recruitment agencies are asked not to respond to this job posting.