Research Jobs at San Diego State University with Visa Sponsorship
Research roles at San Diego State University span faculty-supported projects, sponsored labs, and grant-funded positions across science, social science, and health disciplines. SDSU has an established process for sponsoring international researchers, making it a viable target if you're navigating H-1B, OPT, or other work authorization pathways.
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The pay rate for this position is $22.00 per hour depending upon qualifications and is non-negotiable.
The successful candidate will collaborate within a multidisciplinary team, contributing domain knowledge and technical expertise to develop, implement, and maintain artificial intelligence (AI) and machine learning (ML) models and applications. This role involves working across the data pipeline—from data acquisition and preprocessing to model development and evaluation—while supporting broader analytical needs within the team. The position requires strong problem-solving skills, attention to data quality, and the ability to translate complex data into actionable insights.
Responsibilities:
- Data Acquisition and Management
- Develop and implement automated data extraction pipelines from structured and unstructured data sources (e.g., databases, APIs, web scraping).
- Ensure data integrity, consistency, and proper documentation of data sources and workflows.
-
Maintain and update datasets to support ongoing model development and analysis.
-
Data Cleaning and Pre-processing
- Perform data cleaning, transformation, and normalization to prepare datasets for analysis and modeling.
- Handle missing, inconsistent, or noisy data using appropriate statistical and computational methods.
-
Engineer and select relevant features to improve model performance.
-
Machine Learning Model Development
- Design, build, and optimize machine learning and statistical models for predictive and/or descriptive tasks.
- Select appropriate algorithms based on problem type, data characteristics, and performance requirements.
-
Conduct hyperparameter tuning and model optimization.
-
Model Evaluation and Validation
- Evaluate model performance using appropriate metrics (e.g., accuracy, precision/recall, RMSE, AUC).
- Perform cross-validation and robustness checks to ensure generalizability.
-
Document model assumptions, limitations, and performance outcomes.
-
Data Analysis and Insight Generation
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
- Generate visualizations and summaries to communicate findings effectively.
-
Support decision-making by translating analytical results into actionable insights.
-
Collaboration and Team Support
- Work closely with team members, including domain experts and stakeholders, to understand project requirements and objectives.
- Assist with ad hoc data analysis requests and contribute to ongoing research or product development efforts.
-
Participate in team meetings, code reviews, and documentation practices.
-
Documentation and Reproducibility
- Maintain clear and comprehensive documentation of data pipelines, modeling processes, and analytical workflows.
- Ensure reproducibility of analyses and models through version control and best practices.
Other Duties as assigned (5%)
MINIMUM QUALIFICATIONS
EDUCATION/EXPERIENCE
None
PREFERRED QUALIFICATIONS
- Prior experience in developing end-to-end machine learning pipelines or applications.
- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
- Experience with version control systems (e.g., Git).
- Domain knowledge relevant to the team’s focus area.
ADDITIONAL APPLICANT INFORMATION
- Candidate must reside in California and live within a commutable distance from SDSU at time of hire.
- Job offer is contingent upon satisfactory clearance based on background check results (including a criminal record check).
San Diego State University Research Foundation is an equal opportunity employer. Consistent with California law and federal civil rights laws, SDSU Research Foundation provides equal opportunity in employment without unlawful discrimination or preferential treatment based on race, sex, color, ethnicity, or national origin or any other categories protected by federal or state law.
Employment decisions are based on an individual’s qualifications as they relate to the job under consideration. Our commitment to equal opportunity means ensuring that every employee has equal access to resources and support.
SDSU Research Foundation complies with Titles VI and VII of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, the Americans with Disabilities Act (ADA), Section 504 of the Rehabilitation Act, the California Equity in Higher Education Act, California’s Proposition 209 (Art. I, Section 31 of the California Constitution), and other applicable state and federal anti-discrimination laws including grant or contract terms and conditions related to funded program activities. Further, the SDSU Research Foundation maintains a Nondiscrimination Policy that prohibits discriminatory preferential treatment, segregation based on race or any other protected status, and all forms of unlawful discrimination, harassment, and retaliation in all programs, policies, and practices.
SDSU Research Foundation makes all employment decisions including, but not limited to, applicant screening, hiring, promotion, demotion, compensation, benefits, disciplinary actions, and terminations on the basis of merit.
Overview:
The pay rate for this position is $22.00 per hour depending upon qualifications and is non-negotiable.
The successful candidate will collaborate within a multidisciplinary team, contributing domain knowledge and technical expertise to develop, implement, and maintain artificial intelligence (AI) and machine learning (ML) models and applications. This role involves working across the data pipeline—from data acquisition and preprocessing to model development and evaluation—while supporting broader analytical needs within the team. The position requires strong problem-solving skills, attention to data quality, and the ability to translate complex data into actionable insights.
Responsibilities:
- Data Acquisition and Management
- Develop and implement automated data extraction pipelines from structured and unstructured data sources (e.g., databases, APIs, web scraping).
- Ensure data integrity, consistency, and proper documentation of data sources and workflows.
-
Maintain and update datasets to support ongoing model development and analysis.
-
Data Cleaning and Pre-processing
- Perform data cleaning, transformation, and normalization to prepare datasets for analysis and modeling.
- Handle missing, inconsistent, or noisy data using appropriate statistical and computational methods.
-
Engineer and select relevant features to improve model performance.
-
Machine Learning Model Development
- Design, build, and optimize machine learning and statistical models for predictive and/or descriptive tasks.
- Select appropriate algorithms based on problem type, data characteristics, and performance requirements.
-
Conduct hyperparameter tuning and model optimization.
-
Model Evaluation and Validation
- Evaluate model performance using appropriate metrics (e.g., accuracy, precision/recall, RMSE, AUC).
- Perform cross-validation and robustness checks to ensure generalizability.
-
Document model assumptions, limitations, and performance outcomes.
-
Data Analysis and Insight Generation
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
- Generate visualizations and summaries to communicate findings effectively.
-
Support decision-making by translating analytical results into actionable insights.
-
Collaboration and Team Support
- Work closely with team members, including domain experts and stakeholders, to understand project requirements and objectives.
- Assist with ad hoc data analysis requests and contribute to ongoing research or product development efforts.
-
Participate in team meetings, code reviews, and documentation practices.
-
Documentation and Reproducibility
- Maintain clear and comprehensive documentation of data pipelines, modeling processes, and analytical workflows.
- Ensure reproducibility of analyses and models through version control and best practices.
Other Duties as assigned (5%)
MINIMUM QUALIFICATIONS
EDUCATION/EXPERIENCE
None
PREFERRED QUALIFICATIONS
- Prior experience in developing end-to-end machine learning pipelines or applications.
- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
- Experience with version control systems (e.g., Git).
- Domain knowledge relevant to the team’s focus area.
ADDITIONAL APPLICANT INFORMATION
- Candidate must reside in California and live within a commutable distance from SDSU at time of hire.
- Job offer is contingent upon satisfactory clearance based on background check results (including a criminal record check).
San Diego State University Research Foundation is an equal opportunity employer. Consistent with California law and federal civil rights laws, SDSU Research Foundation provides equal opportunity in employment without unlawful discrimination or preferential treatment based on race, sex, color, ethnicity, or national origin or any other categories protected by federal or state law.
Employment decisions are based on an individual’s qualifications as they relate to the job under consideration. Our commitment to equal opportunity means ensuring that every employee has equal access to resources and support.
SDSU Research Foundation complies with Titles VI and VII of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, the Americans with Disabilities Act (ADA), Section 504 of the Rehabilitation Act, the California Equity in Higher Education Act, California’s Proposition 209 (Art. I, Section 31 of the California Constitution), and other applicable state and federal anti-discrimination laws including grant or contract terms and conditions related to funded program activities. Further, the SDSU Research Foundation maintains a Nondiscrimination Policy that prohibits discriminatory preferential treatment, segregation based on race or any other protected status, and all forms of unlawful discrimination, harassment, and retaliation in all programs, policies, and practices.
SDSU Research Foundation makes all employment decisions including, but not limited to, applicant screening, hiring, promotion, demotion, compensation, benefits, disciplinary actions, and terminations on the basis of merit.
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Get Access To All JobsTips for Finding Research Jobs at San Diego State University Jobs
Align your credentials to SDSU's research priorities
SDSU's sponsored research portfolio leans heavily on federal grants from NIH, NSF, and DOD. Tailor your CV to reflect grant-relevant experience and publications in fields where SDSU has active funding, since hiring managers evaluate research fit before initiating any sponsorship conversation.
Target positions tied to active grant funding
Postdoctoral and research staff roles at universities live and die by grant cycles. Search SDSU's research foundation job board alongside the main HR portal, because grant-funded positions have dedicated budgets that make sponsorship far more straightforward to approve.
Use Migrate Mate to filter SDSU research openings by visa type
Not every SDSU research posting explicitly states sponsorship eligibility. Use Migrate Mate to filter open Research roles at SDSU by the visa types they've sponsored, so you're only spending time on positions that realistically fit your authorization situation.
Clarify OPT cap-gap exposure before accepting an offer
If you're transitioning from F-1 OPT and SDSU files your H-1B for the October 1 start date, confirm your OPT expiration relative to that date. A gap between OPT expiration and October 1 requires timely cap-gap protection, and SDSU's HR team will need your I-20 and EAD details early.
Understand SDSU's PERM labor certification timeline for permanent roles
For research positions that could lead to an EB-2 or EB-3 Green Card, USCIS and DOL require PERM labor certification before the immigrant petition. This process takes a year or more, so raise long-term sponsorship interest during the offer stage, not after onboarding.
Verify SDSU's E-Verify enrollment before your start date
SDSU participates in E-Verify as a federal contractor, which affects I-9 verification timing. Confirm your work authorization document is valid on day one, because E-Verify requires the employer to initiate the case within three business days of your start date.
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Find Research at San Diego State University JobsFrequently Asked Questions
Does San Diego State University sponsor H-1B visas for Researchs?
Yes, San Diego State University sponsors H-1B visas for qualifying Research positions. Sponsorship is most common for postdoctoral researchers, research scientists, and grant-funded staff roles where the position meets the H-1B specialty occupation standard. SDSU's international office manages the petition process, and sponsorship is typically initiated after a formal offer is extended.
How do I apply for Research jobs at San Diego State University?
Applications go through SDSU's official HR portal at careers.sdsu.edu, and some grant-funded research roles are posted separately through the SDSU Research Foundation. Migrate Mate also surfaces open Research positions at SDSU filtered by visa sponsorship type, which helps you identify relevant openings faster. Tailor your CV to the specific research area and funding source listed in the posting.
Which visa types does San Diego State University commonly use for Research roles?
SDSU sponsors H-1B visas for research staff and postdocs in specialty occupations, and supports F-1 OPT and CPT for students in research assistantships. TN status is available for Canadian and Mexican nationals in qualifying research disciplines. For permanent positions, SDSU has filed EB-2 and EB-3 petitions, typically beginning with PERM labor certification through the DOL.
What qualifications does San Diego State University expect for Research positions?
Requirements vary by role, but most research positions expect at minimum a master's degree in a relevant field, with doctoral degrees required for senior research scientist or postdoctoral roles. Demonstrated experience with grant-funded projects, peer-reviewed publications, and proficiency in field-specific methodologies carry significant weight. Positions tied to federal contracts may also require specific security or compliance clearances.
How do I know if a Research role at SDSU will realistically lead to H-1B sponsorship?
The strongest indicator is whether the position is grant-funded and whether the posting explicitly lists visa sponsorship. Roles funded through federal grants from agencies like NIH or NSF have dedicated budget lines that make sponsorship approvals more routine. If a posting is ambiguous, ask the hiring contact directly during the screening call before investing time in a full application.
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