When new treatment methods for cancer are to be evaluated, it is essential to have measurement tools for evaluating the effect of given treatment and early in the disease predicting the future clinical course. This project (https://www.swecris.se/betasearch/details/project/201804375vr) aims at reaching this goal by using medical imaging data and new machine learning methods. Techniques to be tested include segmentation algorithms based on deep learning (deep convolutional neural networks) and generative techniques such as generative adversarial networks (GAN). The workplace will be MTH’s Division of biomedical imaging, an international and cross-disciplinary research environment located in Flemingsberg, adjacent to Karolinska university hospital Huddinge.
Supervision: The doctoral student will be supervised by professor Örjan Smedby[mailto:firstname.lastname@example.org], originally a medical doctor (radiologist) but now the leader of KTH’s research group in medical image processing and visualization, and docent Chunliang Wang, researcher within medical image processing with a special focus on deep learning.
Deadline for applications: 8 June, 2020
For further info and application, see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:331004