PhD: Deep Learning for Medical Image Analysis

Thursday 11th July 2019

Heidelberg University Hospital

Description: Progress and innovation are essential for promising medical treatment. Hundreds of doctors and scientists at Heidelberg University Hospital and its partner research institutes, such as the world-renowned German Cancer Research Center, pursue a common aim: the development of new forms of therapy and their quick implementation for the benefit of the patient. With its 43 specialized clinical departments Heidelberg University Hospital is one of the leading medical centers in Europe. 

The Department of Neuroradiology performs more than 25,000 cross-sectional (CT and MRI) scans per year. It maintains an active research program, dedicated to the development of innovative technologies and their clinical application with the aim of improving patient diagnosis and treatment. It acts as the central study coordinator for multicenter studies on brain tumors, stroke, and multiple sclerosis. For brain tumors, it is the reference center for the German Glioma Network and part of the steering committee of the European Organization for Research and Treatment of Cancer (EORTC).
This unique position will continue our ongoing interdisciplinary research efforts in applying deep-learning techniques to computed tomography (CT) and magnetic resonance imaging (MRI) data for solving clinically relevant questions in the field of Neuroradiology. This includes the development of deep-learning models for predicting treatment outcome in patients with stroke (funded through EUROSTARS), predicting molecular parameters in brain tumors, classification of disease entities based on MRI as well as developing software infrastructure for applying deep-learning algorithms in multicenter clinical trials (funded through the collaborative research center (SFB-1389) of the German Research Council (DFG)). Embedded within a highly-motivated research group (with interdisciplinary collaborations both on the campus as well as internationally) you´ll have access to several established, curated (and segmented) large-scale imaging databases (including annotation on clinical and molecular data) for model development and existing infrastructure with availability of state-of-the-art CPU and GPU servers (e.g. several NVIDIA Tesla GV100 units).
We are seeking a PhD candidate with MSc degree (or equivalent) preferentally in physics, coding skills in Python and experience designing and implementing deep-learning algorithms (e.g. using Tensorflow / Keras / PyTorch), eager to work in the medical field to solve clinically relevant questions using deep learning and excellent command of spoken and written English and / or German.
Highly motivated applicants with an excellent academic record, interested in this interdisciplinary PhD should send an email (Subject line: PhD application) describing their interest and research experience as well as a CV, and / or any inquiries to

Compensation according to TV-L E13 (100%)

Closing Date: 31/08/2019


Heidelberg University Hospital


Heidelberg, Germany


PhD: Deep Learning for Medical Image Analysis