Neuroimaging Technician/Postdoctoral Position at MGH/Harvard Medical School
A.A. Martinos Center for Biomedical Imaging (MGH/Harvard Medical School)
January 22, 2018
45000.00 - 65000.00
Full Time - Experienced
Academic / Research
4 Year Degree
SEEKING STUDY COORDINATOR FOR NEUROIMAGING STUDY
PROTECTING THE AGING BRAIN
Applications are invited for a postdoctoral research fellow position at the A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School (Boston Massachusetts, USA).
The Technican or Postdoctoral Fellow will support the Laboratory for Computational Neurodiagnostics (www.lcneuro.org). The incumbent will function as Study Coordinator for a newly funded neuroimaging study: Protecting the Aging Brain: Self-Organizing Networks and Multiscale Dynamics Under Energy Constraints. The project integrates computational neuroscience modeling with pharmacological intervention and neuroimaging data, in order to understand, predict, and ameliorate the impact of metabolic changes associated with brain aging.
The Study Coordinator’s primary responsibilities will be subject recruitment and data collection (7T fMRI, DTI, MRS, and PET), but with opportunities for data processing/analysis and co-authorship of manuscripts.
The project is based at the Laufer Center for Physical and Quantitative Biology at Stony Brook University (Stony Brook NY). However, the Study Coordinator will be based in Boston MA, where all data collection will occur at the A.A. Martinos Center for Biomedical Imaging (Massachusetts General Hospital/Harvard Medical School). Because the Study Coordinator will be independently coordinating across medical teams, patients, and scanning—as well as interfacing with collaborating institutions—the position requires a high level of discretion, judgment, collaboration and initiative to accomplish goals. We seek someone who has strong organizational and interpersonal skills, and who is meticulous about data quality and procedures.
B.S. (for Technician) or PhD/MD (for Postdoctoral Fellow) in cognitive neuroscience, biomedical engineering, psychology, radiology, or related discipline.
Minimum 2 years (for Technician ) or 3 years (for Postdoc) of full time directly related experience with clinical research.
Minimum 2 years (for Technician) or 3 years (for Postdoc) of full time directly related experience with neuroimaging (fMRI, DTI, MRS, and/or PET). Must be able to independently run a Siemens MRI scanner.
An ideal candidate will have experience with neuroimaging quality assurance (optimization of acquisition parameters), clinical trials, and working with the elderly.
The minimum required commitment is two years, but may be extended upon request.
Additional Salary Information: Average salary is anticipated to be $52,000 (commensurate with experience).
Internal Number: Keck001
About A.A. Martinos Center for Biomedical Imaging (MGH/Harvard Medical School)
LCNeuro's research focuses on the application of control systems engineering and dynamical systems to human neuroimaging time series (fMRI, MEG, EEG, NIRS, ECOG), with neurodiagnostic applications to neurological and psychiatric disorders. Parallel development of instrumentation complements our analytical approaches by optimizing brain time series for dynamic fidelity. One of LCNeuro’s primary goals is to identify key points of failure in the regulation of neural control circuits which, depending upon how they break, lead to signs and symptoms that cluster as distinct psychiatric diagnoses. As a test case for this approach, we are working to understand how the prefrontal-limbic circuit “computes” potential threat in the face of incomplete sensory data, across a clinical spectrum that ranges from pathological fear (generalized anxiety disorder, phobia, PTSD, paranoid schizophrenia) to recklessness. A second direction at LCNeuro considers fMRI connectivity as the solution to an optimization problem imposed, in part, by metabolic constraints at the mitochondrial scale. Theoretically, we use biomimetic modeling to predict trajectories, based on biological “rules” of energy optimization..., which are then validated against data. Experimentally, we expand and contract neurons’ access to energy while observing consequent self-organization and reorganization of networks. We hope that that this work will have important implications for understanding brain aging; specifically, the epidemiologically observed impact of insulin resistance on cognitive decline. A third arm of our research works on maximizing signal/noise for fMRI data, using a combination of acquisition parameters and artifact-removal. Both require access to a “ground truth” for time series dynamics, which led to our invention (with Helmut Strey, Ph.D.) of a patent-pending calibration device (“fMRI dynamic phantom”), currently in commercial partnership with ALA Scientific Instruments, Inc.