Post-Doctoral Fellowship in Multi-Parametric MRS

Johns Hopkins, founded in 1876, is America's first research university and home to nine world-class academic divisions working together as one university.

Salary: $63,480

Johns Hopkins University: School of Medicine: Department of Radiology and Radiological Science: Magnetic Resonance Research

Description

The Group for advanced MRS, led by Prof. Helge Zöllner at Johns Hopkins University, invites applications for a three-year Post-Doctoral Fellowship. The fellow will develop open-source methods for advancing multi-parametric MR spectroscopy including implementation of novel acquisition and analysis methods for clinical 3T MRI systems and application in aging research. This project will develop and apply advanced MRS methods for fast quantification of concentration and relaxation times to track changes in a large cohort of healthy aging volunteers. The proposed methods can be applied in a wide range of pathologies where simultaneous changes in structure and biochemistry are expected to improve the interpretability of MRS.

Key Responsibilities:

• Assessing changes in biochemical profiles across the age range:
  1. Scan healthy volunteers (20 – 80 years) at 3T MRI
  2. Analyze multi-parametric MRS data in Osprey
• Develop and implement analysis methods for multi-parametric MRS in Osprey
  1. Advance existing, in-house analysis methods for multi-parametric MRS
  2. Develop novel approaches for 2D linear-combination modeling
  3. Contribute novel developments to Osprey MRS toolbox
• Test and validate developed methods on the available MRI scanners, including:
  • Two custom-built low-field MRI systems (0.26T and 0.35T).
  • A commercial prototype 50mT Halbach scanner.
• Collaborate with other researchers in the Division, external collaborators or Osprey users.

Qualifications

• Ph.D. in Physics, Medical Physics, Biomedical Engineering, Neuroscience, Computer Science, or a related field.
• Strong background in MR physics, including pulse sequence design, image reconstruction, and signal processing.
• Interest in deep learning techniques applying machine learning to medical imaging.
• Experience with MR spectroscopy is highly desirable.
• Strong programming skills in MATLAB, Python, or similar.
• Ability to work independently as well as in a collaborative research environment.

Application Instructions

Interested candidates should submit the following documents:

• A detailed CV.
• A cover letter describing your relevant research experience and career goals.
• Contact information for two professional references.

Contact Information: For further details, please contact Prof. Helge Zöllner at hzoelln2@jhu.edu.