Assistant Director, MEG Facility

Vanderbilt University•Nashville, TN

10h

About The Position

The Assistant Director, MEG Facility provides scientific, technical, and operational leadership for the Magnetoencephalography (MEG) facility within the College of Connected Computing. This role integrates facility oversight, advanced neuroimaging expertise, research infrastructure development, and independent scientific leadership. The incumbent ensures the reliable operation of the MEG system, develops and maintains advanced data acquisition and analysis pipelines, trains researchers to independent operator status, facilitates cutting-edge interdisciplinary research and develop their own research agenda. In parallel, the position contributes to high-impact publications, grant development, and the strategic growth of NeuroAI research at Vanderbilt University. The College of Connected Computing (CCC) is Vanderbilt's interdisciplinary hub for advancing research and education at the intersection of computing, neuroscience, engineering, and data science. The MEG facility serves as a core platform for high-resolution measurement of brain dynamics, supporting collaborative research across NeuroAI, cognitive neuroscience, and related domains.

Requirements

PhD in Neuroscience, Cognitive Science, Biomedical Engineering, or related field is necessary.
5 to 7 years of relevant experience
Demonstrated expertise in MEG acquisition and analysis
Experience developing neuroimaging pipelines and handling large datasets
Track record of peer-reviewed publications
Experience training or mentoring researchers
Strong programming skills (Python, MATLAB, or equivalent)

Nice To Haves

Experience managing or coordinating a neuroimaging facility
Expertise in advanced MEG analyses (e.g., source reconstruction, time × frequency analyses, connectivity, time-resolved decoding, information-theoretic approaches, reverse engineering of linear and nonlinear computations)
Experience integrating neuroimaging with computational modeling or AI
Track record of supervising interdisciplinary research
Track record of methodological or tool development

Responsibilities

Direct day-to-day operation, maintenance, and quality assurance of the MEG system
Ensure compliance with safety, regulatory, and data governance standards
Manage scheduling, usage, and optimization of facility resources
Interface with vendors, engineers, and institutional support services
Train and certify researchers (faculty, postdocs, students) as MEG operators
Develop training protocols, documentation, and best practices
Provide ongoing technical support for data acquisition and experimental setup
Promote high standards of autonomy and reproducibility across users
Develop, implement, and maintain scalable MEG data processing pipelines
Organize and manage large-scale neuroimaging datasets
Ensure reproducibility, standardization, and integration with computational workflows
Support advanced analytical methods and integration with AI models
Collaborate with investigators to design and implement MEG experiments
Provide expertise in experimental design, signal processing, and analysis
Support interdisciplinary grant proposals and research initiatives
Expand the methodological capabilities of the MEG facility
Develop and lead an independent research programme using MEG
Publish in high-impact peer-reviewed journals
Contribute to grant applications as PI or Co-I
Advance methodological and conceptual innovation in NeuroAI
Contribute to institutional service and facility strategy
Participate in committees and collaborative initiatives
Other duties as assigned