PhD Position in Lower-Field Cardiac Magnetic Resonance Imaging
Job description
The position concerns MR pulse sequence design and image reconstruction, data inference and fusion using classical and physics-informed machine learning approaches to advance time-resolved morphological and functional imaging of the heart.
The work will involve numerical simulations, experimental measurements and applications on volunteers. Together with the team and clinical partners, example data in patients will be obtained to populate digital twins and to indicate the diagnostic value of lower-field deep CMR imaging.
Profile
You hold a Master of Science degree with first-class grades in :
- electrical engineering
- biomedical engineering
- computer science
- physics
You have developed a keen interest in medical imaging physics, signal and data processing. Very good programming skills (C, Matlab / Python, TensorFlow / PyTorch) and a passion for both theoretical and practical work are a premise.
The ability to develop own lines of thought, critically interpret data and a drive to innovate are further requirements along with curiosity, open mindedness, team player and communication skills.
Workplace
Workplace
We offer
We are a dynamic and international team embedded in both electrical engineering and the medical faculty, with a long-standing track record in CMR research.
First-class infrastructure is available, including experimental and clinical MR systems fully dedicated to research, state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU) and workshops for mechanical, electrical and electronic development projects.
Long-standing and very successful cooperations with industry and clinical partners (cardiology, radiology) offer opportunities for networking as well as for deployment of research results in real-world applications.
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We value diversity
In line with to find out how we ensure a fair and open environment that allows everyone to grow and flourish.
Curious? So are we.
We look forward to receiving your online application including :
- motivation letter
- detailed CV
- study subjects including grades and
- contact information of two referees
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
For further information about the position and the group please contact Prof Dr Sebastian Kozerke by e-mail : (no applications) or visit our website.
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