Background
The Diagnostic Image Analysis Group develops computer algorithms to aid clinicians in the interpretation of medical images and further clinical data and thereby improving the diagnostic and treatment process.
We live in a data-driven era where more and more data are being collected. This trend does not stop at the hospital. During the diagnosis and treatment of a patient, a variety of multimodal data is acquired and supplemented by reports, clinical notes, and data from patient visits. Consequently, combining and evaluating all this data is becoming an increasingly difficult task that can hardly be done manually. With yearly increases in, e.g., the number of imaging studies conducted, the workload for healthcare professionals increases. Therefore, there is an urgent need for systems that support clinicians during the diagnosis and treatment process.
Job description
We are looking for PhD students to develop deep-learning algorithms that analyse images and additional data with the aim that these algorithms will support clinicians in diagnosis and treatment process. The applications can range from radiology, oncology, cardiology, radiotherapy or neurology.
Profile
You should - be a creative and enthusiastic researcher with an MSc degree in Computer Science, Physics, Engineering or Biomedical Sciences or similar - have a clear interest to develop image analysis algorithms and an affinity with medical topics. - have experience with deep learning, machine learning, and image analysis is a plus. - have good communication and enjoy working in a multidisciplinary team - have expertise in software development, preferably in Python, are essential.
Terms of employment
You will be appointed for four years as a PhD student with the standard salary and secondary conditions for PhD students in the Netherlands. The research should result in a PhD thesis.
Organization
You will work in the Diagnostic Image Analysis Group (DIAG) DIAG is part of the Departments of Imaging, Pathology, Ophthalmology, and Radiation Oncology of Radboud University Medical Center. We develop computer algorithms to interpret and process medical images. The group currently consists of around 70 researchers. Radboud University Medical Center and Radboud University are located in Nijmegen, 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.
Information
For more information please contact Bram van Ginneken by e-mail.
Application
Use the Apply button on this page to apply for this position. You should supply a motivation letter, your CV, links to a Google Scholar profile, a list of grades and courses you have followed including online courses on deep learning and similar topics, and links to any publications you have written plus any code you have written and is publicly accessible, e.g., on a GitHub account. This application will remain open until the position has been filled. Applications are processed immediately upon receipt.
