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Post-Doctoral Fellowship in Multi-Parametric MRS Faculty

Job in Baltimore, Anne Arundel County, Maryland, 21276, USA
Listing for: Johns Hopkins University
Full Time position
Listed on 2026-06-18
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist
  • Healthcare
    Data Scientist
Salary/Wage Range or Industry Benchmark: 63480 USD Yearly USD 63480.00 YEAR
Job Description & How to Apply Below
Position: Post-Doctoral Fellowship in Multi-Parametric MRS - #Faculty

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:

  • Scan healthy volunteers (20 - 80 years) at 3T MRI

  • Analyze multi-parametric MRS data in Osprey

  • Develop and implement analysis methods for multi-parametric MRS in Osprey

  • Advance existing, in-house analysis methods for multi-parametric MRS

  • Develop novel approaches for 2D linear-combination modeling

  • 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.

  • 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.

Salary: $63,480

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Total

Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: (Use the "Apply for this Job" box below)..

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristics. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors or demographic characteristics that are irrelevant to the program involved.

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.

For further details, please contact Prof. Helge Zöllner at hzoelln
2.

Job Type: Full Time

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