The Quantitative MR Imaging Science (QIS) lab is an interdisciplinary team of experts in physics, medical engineering, mathematics and optimization theory. We specialize in MR image acquisition, including programming of MRI scanner software, and image reconstruction, using in-house developed software to process MRI raw data. This project focusses on deep learning image reconstruction and is part of the Center for Artificial Intelligence in Medicine (CAIM) institute. It is led by Dr. Eva Peper in collaboration with Prof. Dr. Christoph Gräni.

Development of a neural network for image recons

• Development of a neural network for cardiac image reconstruction
• Implementation and testing in an experimental setting and on a clinical MRI scanner in collaboration with our team
• Learn about MRI image reconstruction and data analysis
• Work on experimental designs, research protocols and preparation of reports, presentations and other deliverables

Requirements

• M.Sc. or B.Sc. with a background in engineering, physics, mathematics or similar
• Experience in data analysis with MATLAB and/or Python is required
• Knowledge of deep learning and optimization theory is a plus
• Excellent analytical and problem-solving skills, effective communication skills, and the ability to work both independently and in a team

Benefits

Collaboration with cardiologists and industrial partners, experienced mentors with consistent and friendly supervision, low hierarchies and open discussions, flexible working environment, and a supportive and knowledgeable team. Interested candidates should submit a CV and a brief cover letter outlining their research interests and relevant experience by 9th December 2024.

Questions about the job?

for further information please contact Dr. Eva Peper PostDoc

Write an email

+41 31 632 82 05