The Laboratory for Ophthalmic Image Analysis (OPTIMA) of the Medical University of Vienna is searching for exceptionally motivated Postdocs and PhD students to strengthen the interdisciplinary team working on machine learning for Medical Image Analysis and Computing.

General description: As part of a new initiative on Artificial Intelligence in Retina the successful candidates will participate on exciting projects, at the interface of machine learning and medicine (see our recent review paper: https://bit.ly/2MREzTd). Both of the positions are opened immediately until filled, and early applications will be given priority. We would like to explicitly encourage female candidates to apply!

More information and applications here.

Successful candidates will be immersed into an interdisciplinary environment working closely with a team of computer scientists, software engineers and medical doctors and have many opportunities to learn and grow. Advancements will have a real world impact on clinical management of patients suffering from retinal diseases, a leading cause of blindness today.

Postdoc in Machine Learning for Medical Image Analysis:

We are seeking exceptionally motivated postdocs to strengthen our interdisciplinary team working on machine learning for medical image analysis. The focus of the research is on automated characterization of retinal pathology from 3D optical coherence tomography (OCT) images of human retina, and on learning to predict patient-specific disease progression from a very large-scale curated imaging data and electronic health records. The goal is to enable an effective AI-based clinical decision support for retinal specialist, in a close collaboration with a leading OCT device manufacturer.

PhD student in Medical Image Computing with Deep Learning:

We are offering a fully funded PhD position. The focus of the research project is on learning and predicting patient-specific disease progression and treatment response from in-vivo imaging (longitudinal series of 3D optical coherence tomography (OCT) images) and non-imaging data (e.g., clinical reports) using medical image analysis and deep learning methods. These data-driven disease-progression models allow to assess individualized risk and prognosis of retinal disease.

Apply here

Deadline: The position is opened immediately until filled, early applications will be given priority.