Post-Doctoral Fellow Multimodal Computational Neuroimaging in Alzheimer's Disease
Monday 15th April 2024
Contact Email for the Job Posting [email protected]
Organization McLean Hospital & Harvard University
Location Belmont, MA
Title Post-Doctoral Fellow Multimodal Computational Neuroimaging in Alzheimer's Disease
URL https://connects.catalyst.harvard.edu/Profiles/display/Person/65562
Closing date Jun 30, 2024
Description A post-doctoral fellow is needed to work on an NIA-funded project that involves combining multi-modal MRI data from several different large scale Human Connectome Project studies to investigate brain structure, function, and physiology in individuals with neuropsychiatric symptoms of Alzheimer’s Disease. The individual will be appointed as a Research Fellow in the Department of Psychiatry at Harvard Medical School and will be based at McLean Hospital in Belmont, MA, near Harvard Square and Boston. The position is full-time and benefits eligible, start date negotiable, starting salary $67,780/year with no previous post-doc experience (+$ for experience). We are seeking someone to start immediately or very soon.
A candidate with expertise in some of the following areas is desired: this position involves primarily computational neuroimaging, including large-scale open access neuroimaging data management, organization and processing; cloud computing for imaging analyses at scale; multimodal MRI data analysis, including diffusion, structural, blood-flow related, and task and resting state functional MRI data; open science practices such as ReproNim; multivariate data driven and machine learning methods. Our project is in the context of NIMH Research Domain Criteria; cognitive and affective neuroscience; and neurobiology of aging, dementia, and neuropsychiatric symptoms. We will provide training as needed to round out expertise for the specific roles on the project.
Additional Opportunities: The post-doctoral fellow will be supported to pursue desired training related to career development, including grant writing, presenting and publishing findings, and attending professional development and scientific workshops, symposia and conferences. We have an excellent record of preparing post-doctoral fellows to become independent investigators on the academic track and will support the fellow to submit their own foundation grants, NIH K grants, etc.
Individuals from underrepresented racial and ethnic groups, individuals with disabilities, those from disadvantaged backgrounds, and women from these backgrounds are strongly encouraged to apply. It is the policy of McLean Hospital to affirmatively provide equal opportunity to all qualified applicants for employment and existing employees without regard to their race, religion, color, national origin, sex, age, ancestry, protected veteran status, disability, sexual orientation, gender orientation or any other basis that would be in violation of any applicable law or regulation.
Minimum Requirements:
• PhD in physics, imaging physics, computer science, biomedical sciences, statistics, computational psychiatry, or a neuroscience-related field with a strong focus on neuroimaging (firm requirement).
• Experience with brain image analysis (firm requirement), including SPM, AFNI, and/or preferably FSL
• Statistical programming (firm requirement), preferably Matlab and/or Python, and Unix shell/scripting experience
• Demonstrated analytical, verbal, and scientific writing skills
• 2-year commitment
Additional Desired Qualifications (or desire to learn):
• Multivariate statistical methods and machine learning methods
• Experience with large open access multi-modal neuroimaging datasets (HCP, ADNI, etc)
• Interest in aging, Alzheimer’s Disease and/or psychiatric disorders in aging
To Apply: For the initial application phase, please send your full CV and a cover letter that briefly describes your research interests and experience and publications related to qualifications as described above to:
Lisa Nickerson, Ph.D.
McLean Imaging Center &
Department of Psychiatry
Harvard Medical School
[email protected]
Names of references will be requested after an initial application review phase is passed.