Human Resources Associate Visa Sponsorship Jobs in Vermont
Human resources associate roles in Vermont are concentrated in Burlington, Montpelier, and the healthcare and higher education sectors, with employers like the University of Vermont Medical Center, GlobalFoundries, and state government agencies driving consistent HR hiring. International candidates seeking visa sponsorship will find the strongest opportunities at larger institutions and multinational employers operating in the state.
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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)
- Postdoctoral degree in a quantitative, computational, neuroscientific, or closely related discipline
- Demonstrated background and hands-on experience in the analysis of longitudinal neuroimaging data (e.g., structural MRI, diffusion imaging) from large, multisite studies
- 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)
- Demonstrated background in complex systems science and its application to neurobiological or psychiatric research
- Advanced proficiency in R and Python for statistical computing and data science applications
- Demonstrated experience applying machine learning methods (e.g., regularized regression, ensemble approaches, supervised classification) within rigorous cross-validation frameworks
- Experience with data management, quality control, and data sharing protocols in the context of large-scale, multi-wave research studies
- Record of peer-reviewed scholarly productivity commensurate with career stage, and strong written and oral communication skills
- 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
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 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
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)
- Postdoctoral degree in a quantitative, computational, neuroscientific, or closely related discipline
- Demonstrated background and hands-on experience in the analysis of longitudinal neuroimaging data (e.g., structural MRI, diffusion imaging) from large, multisite studies
- 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)
- Demonstrated background in complex systems science and its application to neurobiological or psychiatric research
- Advanced proficiency in R and Python for statistical computing and data science applications
- Demonstrated experience applying machine learning methods (e.g., regularized regression, ensemble approaches, supervised classification) within rigorous cross-validation frameworks
- Experience with data management, quality control, and data sharing protocols in the context of large-scale, multi-wave research studies
- Record of peer-reviewed scholarly productivity commensurate with career stage, and strong written and oral communication skills
- 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
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 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
Human Resources Associate Job Roles in Vermont
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Search Human Resources Associate Jobs in VermontHuman Resources Associate Jobs in Vermont: Frequently Asked Questions
Which companies sponsor visas for human resources associates in Vermont?
The most consistent visa sponsors for human resources associate roles in Vermont are larger employers with established HR and immigration infrastructure. These include the University of Vermont and UVM Medical Center, GlobalFoundries (the semiconductor manufacturer in Essex Junction), and larger healthcare networks. Smaller Vermont employers and local nonprofits rarely sponsor visas for associate-level HR positions due to the administrative overhead involved.
Which visa types are most common for human resources associate roles in Vermont?
The H-1B visa is the most common visa for human resources associates in Vermont, provided the role qualifies as a specialty occupation requiring a bachelor's degree in human resources, business, or a related field. Some candidates also come through OPT or STEM OPT extensions after completing U.S. degrees. The TN visa is available for Canadian and Mexican nationals whose qualifications align with eligible business categories.
How to find human resources associate visa sponsorship jobs in Vermont?
Migrate Mate is the most direct way to find human resources associate roles in Vermont where employers are open to visa sponsorship. The platform filters job listings specifically by sponsorship willingness, so you're not applying blind to postings that exclude international candidates. Focusing your search on Burlington-area employers and large institutions like UVM gives you the best odds at the associate level.
Which cities in Vermont have the most human resources associate sponsorship jobs?
Burlington and the surrounding Chittenden County area account for the majority of human resources associate sponsorship opportunities in Vermont. The concentration of healthcare, technology, and higher education employers there drives most of the hiring activity. Montpelier, as the state capital, has some HR roles within state agencies, though those positions rarely offer visa sponsorship. South Burlington and Williston also have employers worth targeting.
Are there state-specific considerations for human resources associate roles in Vermont?
Vermont's small population means the HR job market is narrower than larger states, so competition for sponsored associate roles is concentrated around a handful of major employers. The University of Vermont system and the healthcare sector are the primary pipelines for internationally sponsored HR hires. Vermont also has no large tech cluster, so the sponsorship volume seen in states like California or Texas is not present here.
What is the prevailing wage for sponsored human resources associate jobs in Vermont?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.