
SPAN Postdoctoral Associate
Burlington, VT · HybridFull-time$63–77K/yrSeen todaySeen in employer's feed today
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Job overview
The University of Vermont invites applications for a Postdoctoral Associate in the Department of Psychiatry to lead advanced analyses of large longitudinal neuroimaging datasets, applying Bayesian statistics, causal inference, and machine learning, while managing data quality and collaborating within a multidisciplinary research team.
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Position Details
Advertising/Posting Title SPAN Postdoctoral Associate
Posting Summary
The University of Vermont ( UVM ) Larner College of Medicine invites applications for a Postdoctoral Associate position in the Department of Psychiatry, under the mentorship of Matthew D. Albaugh, Ph.D. This position is supported by a NIDA -funded R01 grant and represents a unique opportunity to engage in methodologically rigorous, high-impact research at the intersection of developmental neuroscience, psychiatric epidemiology, and advanced computational data science. UVM is a Carnegie R1 research university with a sustained institutional commitment to transdisciplinary inquiry and a vibrant intellectual environment anchored by the Neuroscience, Behavior and Health Initiative. Burlington, Vermont — situated on the shores of Lake Champlain between the Green Mountains and Adirondacks — consistently ranks among the most livable and progressive small cities in the United States.
The Postdoctoral Associate will lead cutting-edge analyses leveraging three of the largest multimodal longitudinal neuroimaging datasets in existence — ABCD , IMAGEN , and ENIGMA — to delineate developmental windows of vulnerability to cannabis exposure, characterize longitudinal trajectories of brain and behavioral change, and rigorously assess causal relations among cannabis use, neurodevelopment, and psychiatric outcomes. The successful candidate will bring demonstrated expertise in Bayesian statistical methods and causal inference frameworks (e.g., Bayesian causal networks, cross-lagged panel models, propensity score matching, discordant twin designs), as well as a strong theoretical and applied grounding in complex systems science as it pertains to biological and neuropsychiatric data. Hands-on experience with very large, longitudinal, multisite neuroimaging datasets is essential, as is demonstrated proficiency in neuroimaging data processing and analysis pipelines. The Associate must possess advanced competency in both R and Python, with demonstrated experience applying machine learning methods — including regularized regression, ensemble methods, and supervised classification — within rigorous cross-validation frameworks. Experience with data management, quality control, and data sharing in the context of large-scale, multi-wave studies is required.
Candidates must hold a doctoral degree in a quantitative, computational, or neuroscientific discipline, with a record of peer-reviewed publication commensurate with career stage. The ideal applicant will combine deep methodological sophistication with intellectual curiosity, collaborative acumen, and a commitment to open, reproducible science. This position offers an exceptional training environment, close mentorship from productive and well-funded faculty, and direct access to some of the most powerful datasets in developmental psychiatric neuroscience.
Minimum Qualifications (or equivalent combination of education and experience)
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Postdoctoral degree in a quantitative, computational, neuroscientific, or closely related discipline
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Demonstrated background and hands-on experience in the analysis of longitudinal neuroimaging data (e.g., structural MRI , diffusion imaging) from large, multisite studies
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Strong theoretical and applied grounding in Bayesian statistical methods and causal inference frameworks (e.g., Bayesian causal networks, cross-lagged panel models, propensity score methods, discordant twin designs)
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Demonstrated background in complex systems science and its application to neurobiological or psychiatric research
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Advanced proficiency in R and Python for statistical computing and data science applications
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Demonstrated experience applying machine learning methods (e.g., regularized regression, ensemble approaches, supervised classification) within rigorous cross-validation frameworks
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Experience with data management, quality control, and data sharing protocols in the context of large-scale, multi-wave research studies
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Record of peer-reviewed scholarly productivity commensurate with career stage, and strong written and oral communication skills
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Ability to work both independently and collaboratively within a multidisciplinary research team, and commitment to open, reproducible science
Desirable Qualifications
Support departmental initiatives, assist with occasional teaching or guest lecturing, serve on committees, or attend training sessions as appropriate.
Anticipated Pay Range $63,480 - $77,076, tied to NIH limit, based on years
Other Information
Special Conditions Contingent on continued funding, Occasional evening and/or weekends required (if non-exempt position, may result in overtime), This position is eligible for a hybrid schedule with an option to split time between campus and elsewhere, in accordance with the university telecommuting policy, Background Check required for this position
FLSA Exempt
Union Position No
Posting Details
Position will be posted for a minimum of one week, after which it is subject to removal without notice.
Job Location Burlington, Vermont, United States
Job Open Date 09/10/2026
Job Close Date (Jobs close at 11:59 PM EST.) 09/17/2026
Open Until Filled No
Our Common Ground Statement
The University of Vermont is a welcoming, educationally purposeful community committed to creating an inclusive environment that embraces intellectual diversity and global perspectives. We seek to prepare students to be accountable leaders who will bring to their work a grasp of complexity, effective problem-solving and communication skills, and an enduring commitment to learning and ethical conduct. Members of the University of Vermont community embrace and advance the values of Our Common Ground: Respect, Integrity, Innovation, Openness, Justice, and Responsibility. Staff play a critical role in this effort and the successful candidate will demonstrate a strong commitment to UVM’s mission and advancing Our Common Ground values through the execution of their job duties.
Position Information
Position Title Post Doctoral Associate
Posting Number S6291PO
Department Psychiatry/55750
Position Number 00027979
Percent of Full-Time 1.00
Standard Hours at 1.0 FTE 37.5
Term (months per year) 12
Supplemental Questions
Required fields are indicated with an asterisk (*).
Documents Needed to Apply
Required Documents
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Resume
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Cover Letter/Letter of Application
Optional Documents
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