Post-Doctoral Fellowship in Multi-Parametric MRS

Meyer Entsorgung; Baltimore (MD); On-site; USD 57,132 - 69,828; Full time

Benefits offered by this job

Total rewards package for employees' health and career

Job summary

The Chronicle Of Higher Education, Inc. is offering a post-doctoral fellowship at Johns Hopkins University within the Department of Radiology and Radiological Science. This three-year position focuses on developing open-source methods for advancing multi-parameter MR spectroscopy and analyzing data from 3 T MRI systems, particularly in the context of healthy aging research.

Candidates are expected to hold a Ph.D. in relevant fields and have strong skills in MR physics, deep learning, and programming. The role also involves collaboration with external researchers and using innovative techniques in a cutting-edge research environment.

Qualifications

• Ph.D. in Physics, Medical Physics, Biomedical Engineering or related.
• Strong background in MR physics, including pulse sequence design.
• Experience with MR spectroscopy is highly desirable.

Responsibilities

• Assess biochemical profiles across the age range using 3 T MRI.
• Develop and implement analysis methods for multi-parameter MRS.
• Collaborate with other researchers and Osprey users.

Skills

MR physics

Deep learning techniques

Strong programming skills in MATLAB

Signal processing

Education

Ph.D. in Physics or related field

Tools

MATLAB

Python

Job description

Johns Hopkins University: School of Medicine: Department of Radiology and Radiological Science: Magnetic Resonance Research. This post‑doctoral fellowship offers a three‑year contract for a researcher to develop open‑source methods for advancing multi‑parametric MR spectroscopy, including novel acquisition and analysis techniques for clinical 3 T MRI systems and applications in healthy aging research.

Salary: $63,480.

Key Responsibilities

• Assess biochemical profiles across the age range:
  • Scan healthy volunteers (20–80 years) at 3 T 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 the Osprey MRS toolbox.
• Test and validate developed methods on the available MRI scanners, including:
  • Two custom‑built low‑field MRI systems (0.26 T and 0.35 T).
  • A commercial prototype 50 mT 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.

Benefits

Johns Hopkins offers a total rewards package that supports employees' health, life, career, and retirement. For more information, visit the Johns Hopkins benefits site.

Equal Employment Opportunity Statement

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 demographically irrelevant characteristics that are not relevant to the role.