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Arbeitsgruppe

Medizinische Bild- und Signalverarbeitung - gemeinsame Arbeitsgruppe des Fachbereiches Med. Informatik und Med. Bioinformatik und Systembiologie

Stellenangebote

für den Themenbereich Medizinische Bild- und Signalverarbeitung

14.08.2020

PhD Thesis “CNNs for Medical Image Processing: Learning from Limited Data””

Institution: Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine,
Heidelberg University, Germany
Start date: as soon as possible
Duration: 36 months

Profile:
Applicants will hold a master degree / will be master candidate in physics, computer science, mathematics, biomedical engineering or a related field; strong knowledge in programming and algorithmic development, experience in machine learning and image processing is required; willingness to learn required programming languages (Python),tools for deep learning (TensorFlow) and the principles of medical imaging techniques related to the project is expected.

Project Description:
Deep Learning is a machine learning field that became essential to the field of image processing in the last years. High performance algorithms can be trained on large data sets. However, for rare conditions with a limited number of training cases, training CNNs remains a challenge. The candidate will work on a training pipeline that can be applied to various data sets and tasks. The Research Campus Mannheim Molecular Interventional Environment (M²OLIE) develops innovative molecular imaging technologies by fusion of several imaging modalities (CT, MRI, PET) to enable image-guided, high-precision interventions using high-end CT and robotic systems. The PhD candidate will perform research in deep learning based image segmentation within the Research campus and beyond. The project can be executed in German or English.

Working Environment:
Our group is composed of more than thirty scientists from physics, electrical engineering, medicine and computer science and is working in close co-operation with the local medical departments. We are developing new imaging techniques and data analysis approaches and translate them with our clinical partners into daily practice. Our research team specializes in exploration of Deep Learning in interventional imaging. Ongoing collaborations with other researchers involve the Central Institute of Mental Health (ZI, Mannheim), the German Cancer Research Centre (DKFZ, Heidelberg), and across Europe with multiple opportunities to visit leading international laboratories and to attend taught schools.

Interested?
If you enjoy working in an interdisciplinary, young, creative and open team, we are looking forward to your application! For more information on the project or for application please contact:

Project leader:
Prof. Dr. Ing. Frank Zöllner
Computer Assisted Clinical Medicine,
Medical Faculty Mannheim, Heidelberg University,
Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
Tel.: +49 621 383 5117
E-Mail: frank.zoellner@MedMa.Uni-Heidelberg.de
Web: http://www.ma.uni-heidelberg.de/inst/cbtm/ckm/
Director:
Prof. Dr. rer. nat. Lothar Schad
Chair in Computer Assisted Clinical Medicine,
Medical Faculty Mannheim, Heidelberg University,
Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
Tel.: +49 621 383 5121
E-Mail: Lothar.Schad@MedMa.Uni-Heidelberg.de
Web: www.ma.uni-heidelberg.de/inst/cbtm/ckm/

Offer of employment