Post-Doctoral Fellowship in Multi-Parametric MRS

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.