Post-Doctoral Fellowship in Advanced MR Spectroscopy Full-time

Post-Doctoral Fellowship in Advanced MR Spectroscopy

The research group led by Dr. Georg Oetlzschner at The Johns Hopkins University School of Medicine invites applications for a two-year Postdoctoral Fellowship. The fellow will work on various NIH-funded research projects focused on the development novel data processing and analysis methods for in-vivo MR spectroscopy (MRS) and their application in the human brain. The goals of this work are: (i) to improve the reliability and reproducibility of in-vivo MRS metabolite concentration estimation; (ii) to demonstrate their utility as biomarkers of function and disease; (iii) to disseminate new methods to other researchers worldwide through our collaborative open-source MRS analysis software platform “Osprey”.

Key Responsibilities:

• Advance our newly-developed general linear-combination model.
• Develop appropriate quantitative metrics to evaluate which model is the best one (quantitative information criteria).
• Develop new sampling methods (based on Markov Chain Monte Carlo methods) to solve optimization problems and characterize the uncertainty of the modeling.
• Acquire MRS data in healthy volunteers, as well as patients with brain tumors and other disorders.
• Integrate the newly-developed methods for dissemination via the “Osprey” platforms.
• Contribute to dissemination, maintenance, and user support of the “Osprey” platform.

Beyond this, there will be opportunities to pursue goals such as:

• Develop new MRS/MRI pulse sequences.
• Develop new analysis methods to parametrize and model MRS artefacts such as lipid contamination (and/or eliminate).
• Develop deep-learning-based methods for processing and analysis.
• Develop novel quantification routines specifically suitable for pediatric and/or aging cohorts.

The candidate is expected to:

• Work independently and as a constructive part of a large team of interdisciplinary researchers.
• Follow all key principles of responsible and reproducible research.
• Draft and submit manuscripts for publication in field-leading peer-reviewed journals (e.g., Magnetic Resonance in Medicine).
• Draft and submit abstracts to field-leading annual society meetings (e.g., ISMRM).

Qualifications:

Key Qualifications:

• Ph.D. in Medical Physics, Biomedical Engineering, Electrical Engineering, Computer Science, Neuroscience, or a related field.
• Experience with signal processing, data modelling, non-linear optimization, and MR physics.
• Strong programming skills in MATLAB, Python, R, C++, and/or similar.
• Experience working with MRS data is desirable, but not strictly necessary.
• Ability to work independently as well as in a collaborative research environment.

Preferred Skills:

• Hands-on experience with acquiring and analyzing in-vivo MRS data.
• Knowledge in solving complex optimization problems.
• Knowledge of statistical analysis methods for biomedical research.
• Experience with reproducible research, open science practices, version control (OSF, Git, Docker, Jupyter, R Markdown etc.)
• Strong publication record in relevant fields such as MRI/MRS, NMR spectroscopy, clinical neuroimaging, etc.

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 three professional references.