STEM OPT Artificial Intelligence Scientist Jobs
Artificial Intelligence Scientist roles in machine learning, deep learning, and AI research are among the strongest fits for STEM OPT authorization. Your STEM degree qualifies you for the 24-month extension, giving you up to 36 months total to work for any employer enrolled in E-Verify and willing to file a formal training plan.
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The Buck Institute for Research on Aging is seeking a Data Scientist / AI Scientist to support a research program focused on the fundamental biology of aging through the development and application of advanced artificial intelligence approaches. This role will contribute to efforts that use imaging, quantitative analysis, foundation models, and modern AI to better understand the biological mechanisms of aging and identify new ways to measure, predict, and potentially intervene in those processes. The successful candidate will join a highly collaborative, multidisciplinary team that brings together expertise in biology, biophysics, computer science, artificial intelligence, and other quantitative disciplines. This individual will help develop new computational methods, analyze complex imaging datasets, and work closely with experimental and computational researchers to generate insights from large-scale biological data.
About The Zhou Lab
Our team is intentionally multidisciplinary, bringing together researchers from biology, biophysics, computer science, AI, and other quantitative fields. We see this cross-disciplinary environment as a significant strength, creating opportunities for shared learning, creative problem-solving, and innovation that would be less likely to emerge within a single field alone. Candidates from pure computational science backgrounds (with or without prior experience in bioinformatics) are encouraged to apply. Our lab has the experience of training CS background students to work on biological questions, as our dataset is either images or texts. Prior experience in biological or biomedical imaging is helpful but not required for candidates with strong technical expertise and a genuine interest in applying frontier AI methods to major biological questions.
Recent example of our work:
The Spatiotemporal Proteome Landscape of Aging: Structural determinants of Age-Sensitive Proteome Remodeling (bioRxiv, 2026).
Responsibilities
- Develop and apply advanced AI and machine learning methods to research questions in aging biology
- Design, build, and optimize computational approaches for large-scale image and biological data analysis
- Build and apply models in areas such as computer vision, image recognition, segmentation, deep learning, generative AI, diffusion models, and multimodal or foundation-model approaches
- Analyze complex imaging datasets and extract biologically meaningful patterns and insights
- Collaborate closely with experimental and computational researchers to integrate AI methods with biological research
- Contribute to the design of new research directions at the intersection of AI, imaging, and aging biology
- Contribute to a collaborative and intellectually engaged research environment
Required Qualifications
- BS, MS, or PhD in computer science, data science, artificial intelligence, computational biology, bioengineering, applied mathematics, physics, or a related quantitative field
- Strong experience in one or more of the following areas:
- Computer vision
- Image recognition and segmentation
- Deep learning
- Generative AI
- Diffusion models
- Multimodal or foundation-model approaches
- Demonstrated experience developing computational methods and analyzing complex datasets
- Strong quantitative, analytical, and programming skills
- Ability to work independently and collaboratively in a multidisciplinary research setting
- Strong verbal and written communication skills
Preferred Qualifications
- Experience with biological, biomedical, or microscopy imaging data
- Experience working in interdisciplinary research environments
- Interest in applying cutting-edge AI approaches to fundamental questions in biology and aging
- Publication record, open-source contributions, relevant research, project, or code portfolio
Compensation & Benefits
- $80,000 to $130,000 depending on skills and experience
- Comprehensive benefits including medical/dental/vision coverage, paid time off, paid parental leave, 401(k) employer contribution, and a student debt repayment option
About the Buck
The Buck Institute for Research on Aging is the first independent biomedical research institute in the United States devoted solely to research on aging. Located in Novato, California, the Buck brings together scientists across multiple disciplines to study the mechanisms of aging and age-related disease, to help people live better, longer. The Buck Institute is an equal opportunity employer. We strongly encourage applications from candidates whose experiences and perspectives will contribute to the diversity and excellence of our community.
To Apply
Please submit:
- a curriculum vitae or resume,
- a brief statement of interest, and
- any relevant publications, projects, or code
Position Summary
The Buck Institute for Research on Aging is seeking a Data Scientist / AI Scientist to support a research program focused on the fundamental biology of aging through the development and application of advanced artificial intelligence approaches. This role will contribute to efforts that use imaging, quantitative analysis, foundation models, and modern AI to better understand the biological mechanisms of aging and identify new ways to measure, predict, and potentially intervene in those processes. The successful candidate will join a highly collaborative, multidisciplinary team that brings together expertise in biology, biophysics, computer science, artificial intelligence, and other quantitative disciplines. This individual will help develop new computational methods, analyze complex imaging datasets, and work closely with experimental and computational researchers to generate insights from large-scale biological data.
About The Zhou Lab
Our team is intentionally multidisciplinary, bringing together researchers from biology, biophysics, computer science, AI, and other quantitative fields. We see this cross-disciplinary environment as a significant strength, creating opportunities for shared learning, creative problem-solving, and innovation that would be less likely to emerge within a single field alone. Candidates from pure computational science backgrounds (with or without prior experience in bioinformatics) are encouraged to apply. Our lab has the experience of training CS background students to work on biological questions, as our dataset is either images or texts. Prior experience in biological or biomedical imaging is helpful but not required for candidates with strong technical expertise and a genuine interest in applying frontier AI methods to major biological questions.
Recent example of our work:
The Spatiotemporal Proteome Landscape of Aging: Structural determinants of Age-Sensitive Proteome Remodeling (bioRxiv, 2026).
Responsibilities
- Develop and apply advanced AI and machine learning methods to research questions in aging biology
- Design, build, and optimize computational approaches for large-scale image and biological data analysis
- Build and apply models in areas such as computer vision, image recognition, segmentation, deep learning, generative AI, diffusion models, and multimodal or foundation-model approaches
- Analyze complex imaging datasets and extract biologically meaningful patterns and insights
- Collaborate closely with experimental and computational researchers to integrate AI methods with biological research
- Contribute to the design of new research directions at the intersection of AI, imaging, and aging biology
- Contribute to a collaborative and intellectually engaged research environment
Required Qualifications
- BS, MS, or PhD in computer science, data science, artificial intelligence, computational biology, bioengineering, applied mathematics, physics, or a related quantitative field
- Strong experience in one or more of the following areas:
- Computer vision
- Image recognition and segmentation
- Deep learning
- Generative AI
- Diffusion models
- Multimodal or foundation-model approaches
- Demonstrated experience developing computational methods and analyzing complex datasets
- Strong quantitative, analytical, and programming skills
- Ability to work independently and collaboratively in a multidisciplinary research setting
- Strong verbal and written communication skills
Preferred Qualifications
- Experience with biological, biomedical, or microscopy imaging data
- Experience working in interdisciplinary research environments
- Interest in applying cutting-edge AI approaches to fundamental questions in biology and aging
- Publication record, open-source contributions, relevant research, project, or code portfolio
Compensation & Benefits
- $80,000 to $130,000 depending on skills and experience
- Comprehensive benefits including medical/dental/vision coverage, paid time off, paid parental leave, 401(k) employer contribution, and a student debt repayment option
About the Buck
The Buck Institute for Research on Aging is the first independent biomedical research institute in the United States devoted solely to research on aging. Located in Novato, California, the Buck brings together scientists across multiple disciplines to study the mechanisms of aging and age-related disease, to help people live better, longer. The Buck Institute is an equal opportunity employer. We strongly encourage applications from candidates whose experiences and perspectives will contribute to the diversity and excellence of our community.
To Apply
Please submit:
- a curriculum vitae or resume,
- a brief statement of interest, and
- any relevant publications, projects, or code
See all 439+ STEM OPT Artificial Intelligence Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Artificial Intelligence Scientist Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as an Artificial Intelligence Scientist
Verify your CIP code before applying
Your STEM OPT eligibility depends on your degree's Classification of Instructional Programs code. Computer Science (11.0701), Applied Mathematics (27.0301), and Data Science (30.7001) codes all qualify. Confirm yours on your I-20 before targeting roles.
Check E-Verify enrollment before every application
AI Scientist roles at research labs and startups often lack E-Verify enrollment, which disqualifies them for STEM OPT. Search the E-Verify employer search tool by company name before investing time in any application or interview process.
Target employers with active AI-specific LCA filings
Companies that have filed Labor Condition Applications for AI Scientist or Machine Learning Engineer roles have cleared DOL's prevailing-wage process before. Use Migrate Mate to filter employers by verified filing history so you're focusing on proven sponsors.
Align your I-983 training plan to research outputs
USCIS requires your I-983 to list specific learning objectives tied to your AI Scientist role. Map each objective to deliverables like model architectures, published benchmarks, or deployed systems rather than generic skill categories. Your DSO must sign off before your extension activates.
Use the OFLC Wage Search to benchmark offers early
AI Scientist prevailing wages vary sharply by SOC code and geographic area. Pull the DOL wage level for your exact job title and metro before your first offer conversation so you can evaluate whether the role meets STEM OPT's requirement for bona fide employment.
Time your extension filing around your OPT end date
You must file the STEM OPT extension with USCIS at least 90 days before your initial OPT expires to maintain continuous work authorization. Missing this window forces a gap. Confirm your exact end date on your EAD card and count back from there.
Frequently Asked Questions
Does my degree qualify me for STEM OPT as an Artificial Intelligence Scientist?
Your degree qualifies if it carries a STEM-designated CIP code on your I-20. Degrees in Computer Science, Applied Mathematics, Electrical Engineering, Data Science, and Cognitive Science typically qualify. The role itself does not need to be formally classified as STEM, but your employer must confirm the position uses your STEM training on the I-983. Verify your CIP code with your DSO before filing.
What E-Verify requirement applies to my STEM OPT employer?
Every employer who hires you under the STEM OPT extension must be enrolled in E-Verify at the specific worksite where you'll be working, not just at the company's headquarters. This applies even if you're placed on a research team at a client site or a national lab. Confirm enrollment through the E-Verify employer search before accepting any offer.
What goes into the I-983 training plan for an AI Scientist role?
The I-983 requires you and your employer to document specific learning objectives, supervision structure, and how the role relates to your STEM degree. For AI Scientist positions, objectives should reference concrete research tasks such as developing novel model architectures, running ablation studies, or contributing to peer-reviewed publications. Generic entries like 'improve machine learning skills' are frequently flagged during USCIS review.
How does cap-gap protect my work authorization if I'm selected in the H-1B lottery?
If your employer files an H-1B visa petition on your behalf before your OPT or STEM OPT EAD expires and you're selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that year. Your employment as an AI Scientist can continue uninterrupted during this window. USCIS confirms cap-gap eligibility on its guidance pages, and your DSO updates your I-20 to reflect the extended period.
Where can I find Artificial Intelligence Scientist jobs at E-Verify employers?
Migrate Mate filters AI and machine learning roles specifically by employers who meet STEM OPT requirements, including E-Verify enrollment and prior sponsorship history. This saves you from applying to research positions at companies that can't legally employ you on an extension. You can search by role type, location, and employer filing activity to prioritize the most viable opportunities.