TN Visa Machine Learning Intern Jobs
Machine Learning Intern roles qualify for TN visa sponsorship under the Computer Systems Analyst or Engineer scientist categories when the position requires applying ML frameworks to real data problems. Canadian citizens can enter at the border same-day; Mexican citizens apply at a U.S. consulate. Your employer files no lottery paperwork.
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Get Access To All JobsINTRODUCTION
The Care Health and Reasoning Machines (CHARM) lab led by Dr. Jeremy C. Weiss at the National Library of Medicine seeks to hire a postdoctoral fellow at the intersection(s) of the following research areas: longitudinal machine learning, multi-modal analysis, clinical informatics, and population health.
About the position
The National Library of Medicine (NLM) is one of the 27 institutes at the National Institutes of Health (NIH). NLM is the world’s largest biomedical library and a leader in research, development, and training in biomedical informatics and health information technology. The Division of Intramural Research (DIR) within NLM has two primary research areas: computational health research and computational biology.
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In computational health research, our efforts center on natural language processing (NLP), clinical image analysis, biomedical ontologies, information modeling, and clinical data analytics.
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In computational biology, we emphasize transcriptional regulation, chromatin and network biology, structural and functional analysis, sequence statistics, and evolutionary genomics.
The CHARM lab is investigating methods that learn from longitudinal, textual and tabular data present in health data that (1) are predictive forecasters, and (2) preserve interrogable properties. The research will address the trustworthiness of electronic health records and complementary biomedical data for clinical decision making. Relevant experience includes expertise in representation learning, longitudinal data, annotation, curation, large-language models, and multi-modal learning, with applications in health domains. Relevant programming experience includes pytorch/huggingface/sklearn and R/tidyverse.
Recent relevant publications:
- Wang J, Weiss JC. A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reports. American Medical Informatics Association Informatics Summit. Pittsburgh, 2025.
- Frattallone-Llado G, Kim J, Cheng C, Salazar D, Edakalavan S, Weiss JC. Using Multimodal Data to Improve Precision of Inpatient Event Timelines. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024.
- Noroozizadeh S, Weiss JC, and George Chen. “Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression.” Machine Learning for Health. PMLR. 2023.
Position Overview: This is a full-time postdoctoral fellow position. The initial appointment will be for one year, and is renewable on a yearly basis, with extensions up to 5 years total. The NIH offers a competitive stipend (based on postdoctoral experience, see stipend tables) and a stipend supplement for comprehensive health insurance. The NIH is dedicated to the continued education and career development of all its research staff. Candidates are subject to a background investigation. Explore additional information about NIH postdoctoral fellowships.
What you'll need to apply
Applicants should submit the following materials to Jeremy Weiss, MD, PhD at jeremy.weiss@nih.gov:
- Updated CV
- Cover letter with a short research statement and preferred starting date
- Link(s) to published artifacts (packages, github repositories, etc), and
- Contact information for 3 references (please include the full name with titles, institute, email address and phone number of each reference)
Prospective candidates should include "Postdoc Position Inquiry" and their last name in the email subject line.
Application Deadline: Applications will be accepted and reviewed on a rolling basis until the position is filled.
Contact name: Dr. Jeremy Weiss
Contact email: jeremy.weiss@nih.gov
QUALIFICATIONS
- PhD and/or MD, or equivalent in related subject areas, including machine learning, computer science, medicine, bioinformatics, biomedical informatics and statistics/biostatistics
- Clinical Machine Learning: Programming experience in python, pytorch; R, Julia, and/or C++
- Publishing experience with peer-reviewed journals or conferences in the above areas
INTRODUCTION
The Care Health and Reasoning Machines (CHARM) lab led by Dr. Jeremy C. Weiss at the National Library of Medicine seeks to hire a postdoctoral fellow at the intersection(s) of the following research areas: longitudinal machine learning, multi-modal analysis, clinical informatics, and population health.
About the position
The National Library of Medicine (NLM) is one of the 27 institutes at the National Institutes of Health (NIH). NLM is the world’s largest biomedical library and a leader in research, development, and training in biomedical informatics and health information technology. The Division of Intramural Research (DIR) within NLM has two primary research areas: computational health research and computational biology.
-
In computational health research, our efforts center on natural language processing (NLP), clinical image analysis, biomedical ontologies, information modeling, and clinical data analytics.
-
In computational biology, we emphasize transcriptional regulation, chromatin and network biology, structural and functional analysis, sequence statistics, and evolutionary genomics.
The CHARM lab is investigating methods that learn from longitudinal, textual and tabular data present in health data that (1) are predictive forecasters, and (2) preserve interrogable properties. The research will address the trustworthiness of electronic health records and complementary biomedical data for clinical decision making. Relevant experience includes expertise in representation learning, longitudinal data, annotation, curation, large-language models, and multi-modal learning, with applications in health domains. Relevant programming experience includes pytorch/huggingface/sklearn and R/tidyverse.
Recent relevant publications:
- Wang J, Weiss JC. A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reports. American Medical Informatics Association Informatics Summit. Pittsburgh, 2025.
- Frattallone-Llado G, Kim J, Cheng C, Salazar D, Edakalavan S, Weiss JC. Using Multimodal Data to Improve Precision of Inpatient Event Timelines. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024.
- Noroozizadeh S, Weiss JC, and George Chen. “Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression.” Machine Learning for Health. PMLR. 2023.
Position Overview: This is a full-time postdoctoral fellow position. The initial appointment will be for one year, and is renewable on a yearly basis, with extensions up to 5 years total. The NIH offers a competitive stipend (based on postdoctoral experience, see stipend tables) and a stipend supplement for comprehensive health insurance. The NIH is dedicated to the continued education and career development of all its research staff. Candidates are subject to a background investigation. Explore additional information about NIH postdoctoral fellowships.
What you'll need to apply
Applicants should submit the following materials to Jeremy Weiss, MD, PhD at jeremy.weiss@nih.gov:
- Updated CV
- Cover letter with a short research statement and preferred starting date
- Link(s) to published artifacts (packages, github repositories, etc), and
- Contact information for 3 references (please include the full name with titles, institute, email address and phone number of each reference)
Prospective candidates should include "Postdoc Position Inquiry" and their last name in the email subject line.
Application Deadline: Applications will be accepted and reviewed on a rolling basis until the position is filled.
Contact name: Dr. Jeremy Weiss
Contact email: jeremy.weiss@nih.gov
QUALIFICATIONS
- PhD and/or MD, or equivalent in related subject areas, including machine learning, computer science, medicine, bioinformatics, biomedical informatics and statistics/biostatistics
- Clinical Machine Learning: Programming experience in python, pytorch; R, Julia, and/or C++
- Publishing experience with peer-reviewed journals or conferences in the above areas
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Get Access To All JobsTips for Finding TN Visa Sponsorship as a Machine Learning Intern
Align your transcripts to ML frameworks
TN visa approval hinges on demonstrating a direct link between your degree field and the ML intern role. Pull your unofficial transcript before applications and flag coursework in statistics, neural networks, or data engineering that maps to the job description.
Target employers already filing TN petitions
Search Migrate Mate for employers with recent visa filings who have sponsored Computer Systems Analyst or Engineer roles. Those employers already understand visa sponsorship processes and won't hesitate over whether an ML intern position qualifies for TN status.
Negotiate a support letter before your start date
Canadian citizens need their TN support letter ready at the port of entry, not after onboarding begins. Confirm the employer will issue a detailed offer letter stating your ML duties, degree requirement, and intended duration before you book travel.
Clarify which TN category your role falls under
ML intern postings sometimes blur Computer Systems Analyst and Engineer scientist categories. Ask your hiring manager or recruiter which classification they intend to file under before you reach the offer stage, since the supporting documentation differs between the two.
Use Migrate Mate to filter jobs by visa sponsorship experience
Not every ML internship listing advertises visa support. Use Migrate Mate to surface roles at employers with recent visa filings, so you spend your applications on positions where sponsorship experience is already part of the hiring process.
Prepare for Mexican citizen consular processing timelines
Mexican nationals must schedule a nonimmigrant visa interview at a U.S. consulate before starting work. Build at least four to six weeks into your timeline between offer acceptance and your intended start date to account for appointment availability.
Machine Learning Intern TN Visa: Frequently Asked Questions
Does a Machine Learning Intern role qualify for TN visa sponsorship?
Yes, provided the position genuinely requires a bachelor's degree or higher in a qualifying field such as computer science, engineering, or mathematics. The role must map to an approved TN category, typically Computer Systems Analyst or Engineer scientist. A generic intern title without a clear technical degree requirement can create problems at the port of entry or consulate, so confirm the category with your employer before accepting the offer.
How does TN visa compare to H-1B for Machine Learning Intern positions?
TN has no annual cap and no lottery for Canadian citizens, so you can start as soon as the employer issues a qualifying offer letter and you clear the port of entry. H-1B visa requires lottery selection, a April registration window, and an October 1 start date at the earliest. For internship timelines tied to academic semesters, TN's flexibility makes it far more practical when you're Canadian or Mexican and the role qualifies.
What documents does an employer need to sponsor a TN visa for this role?
The employer must provide a support letter on company letterhead that states the job title, the specific ML duties, the TN category being claimed, your degree and how it relates to the role, and the intended employment period. Canadian citizens present this letter at the U.S. port of entry along with proof of citizenship and their degree credentials. Mexican citizens submit it as part of their DS-160 consular application package.
Where should I search for Machine Learning Intern jobs that offer TN visa sponsorship?
Migrate Mate is built specifically for Canadian and Mexican professionals seeking roles with documented TN visa sponsorship. Most general job boards don't filter by visa category or employer filing history, which means you spend time applying to postings where sponsorship is uncertain. Migrate Mate surfaces ML intern roles at employers who have an established record of supporting TN applicants.
Can a Machine Learning Intern on TN status change employers mid-internship?
You can change employers, but TN status is tied to a specific employer and position. A new TN must be obtained before you begin work with the new company, either through a new port-of-entry entry for Canadians or a consular appointment for Mexican citizens. You cannot simply transfer TN status the way some other visa categories permit, so any employer change requires lead time and coordination with the new hiring team.