Post-Doctoral Fellowship in Advanced MR Spectroscopy

General Description Dr. Georg Oetlzschner’s research group at The Johns Hopkins University School of Medicine invites applications for a two‑year Postdoctoral Fellowship. The fellow will work on NIH‑funded projects focused on developing novel data processing and analysis methods for in‑vivo MR spectroscopy (MRS) and applying them in the human brain. The goals are: Improve the reliability and reproducibility of in‑vivo MRS metabolite concentration estimation. Demonstrate the utility of these methods as biomarkers of function and disease. Disseminate new methods to researchers worldwide through the open‑source MRS analysis platform "Osprey". Key Responsibilities Advance our general linear‑combination model. Develop quantitative metrics (e.g., information criteria) to evaluate model performance. Implement new sampling methods based on Markov Chain Monte Carlo to solve optimization problems and characterize modeling uncertainty. Acquire MRS data from healthy volunteers and patients with brain tumors and other disorders. Integrate new methods into the "Osprey" platform for dissemination. Contribute to maintenance and user support of the "Osprey" platform. Additional Opportunities Develop new MRS/MRI pulse sequences. Create analysis methods to parameterize and model MRS artifacts such as lipid contamination. Design deep‑learning‑based methods for processing and analysis. Develop quantification routines suitable for pediatric and/or aging cohorts. Candidate Expectations Work independently and as part of an interdisciplinary research team. Adhere to responsible and reproducible research principles. Draft and submit manuscripts to peer‑reviewed journals (e.g., Magnetic Resonance in Medicine). Submit abstracts to leading annual society meetings (e.g., ISMRM). Qualifications PhD in Medical Physics, Biomedical Engineering, Electrical Engineering, Computer Science, Neuroscience, or related field. Experience with signal processing, data modeling, non‑linear optimization, and MR physics. Strong programming skills in MATLAB, Python, R, C++, and/or similar languages. Experience working with MRS data is desirable but not required. Ability to work independently and collaboratively. Preferred Skills Hands‑on experience acquiring and analyzing in‑vivo MRS data. Knowledge of solving complex optimization problems. Knowledge of statistical analysis methods for biomedical research. Experience with reproducible research, open science practices, and version control (OSF, Git, Docker, Jupyter, R Markdown). Strong publication record in MRI/MRS, NMR spectroscopy, or clinical neuroimaging. Salary and Benefits The salary range is determined by Johns Hopkins University and may vary based on location, skills, experience, and market conditions. JHU offers a comprehensive total rewards package that supports health, life, career, and retirement. For more information, visit Equal Opportunity Employer The Johns Hopkins University is an equal opportunity employer and does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity, veteran status, or other legally protected characteristic. #J-18808-Ljbffr