OPT Bioinformatics Jobs
Bioinformatics roles sit at the intersection of biology, computer science, and data analysis, making them a strong fit for OPT work authorization. Most positions require a relevant degree in computational biology, bioinformatics, or a related STEM field, which also qualifies you for the 24-month STEM OPT extension.
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The Ocañas Lab is part of the Genes & Human Disease Research Program at OMRF, a nonprofit biomedical research institute in Oklahoma City. Our research investigates how biological sex, aging, and immune regulation influence neurodegenerative and other age-related diseases. Our laboratory combines cutting-edge genomic technologies, experimental biology, and computational approaches to understand how genetic, epigenetic, and environmental factors influence cellular function during aging. We are looking for an individual who enjoys working at the intersection of biology, statistics, and computational science. The ideal candidate will have strong analytical and programming skills, experience with machine learning and predictive modeling, and a genuine interest in understanding the biological questions underlying the data. The successful candidate will work closely with experimental scientists to develop analytical strategies, identify meaningful biological patterns, generate new hypotheses, and contribute to scientific discovery. We particularly value individuals who can think critically about biological mechanisms rather than simply apply established analytical pipelines.
Key Responsibilities:
Bioinformatics and Biological Data Analysis
- Analyze and interpret high-dimensional biological datasets, including bulk RNA-seq, single-cell/single-nucleus RNA-seq, spatial transcriptomics, and DNA methylation sequencing.
- Perform data quality control, normalization, differential expression analysis, pathway enrichment, cell-type characterization, and multi-omics integration.
- Investigate molecular mechanisms, regulatory networks, and cellular heterogeneity associated with aging and disease.
- Integrate genomic, epigenomic, imaging, and behavioral data to identify relationships across biological systems.
Machine Learning and Predictive Modeling
- Develop, evaluate, and interpret machine learning models to identify molecular signatures, classify biological states, and predict experimental or disease-related outcomes.
- Apply supervised and unsupervised approaches, including classification, regression, clustering, feature selection, and dimensionality reduction.
- Assess model performance using appropriate validation strategies, statistical methods, and measures of predictive accuracy.
- Identify biologically meaningful predictors and translate computational findings into testable hypotheses.
- Explore and implement emerging computational approaches for complex biological data analysis.
Scientific Collaboration and Computational Development
- Collaborate with laboratory members to formulate research questions, design analyses, and interpret experimental results.
- Apply statistical and computational approaches to experimental design, including sample size estimation and consideration of biological and technical variables.
- Develop and maintain reproducible analysis pipelines using R, Python, and high-performance computing resources.
- Generate scientific visualizations, figures, and analytical reports.
- Contribute to scientific manuscripts, grant applications, and research presentations.
- Provide computational guidance and training to other laboratory members.
- Stay current with emerging developments in bioinformatics, computational biology, and machine learning.
Minimum Qualifications
- Bachelor’s degree in Bioinformatics, Mathematics, Statistics, Computational Biology, Computer Science, or relevant field and 3 years of relevant experience/training or combination of education and experience.
- Proficiency in R and Python for data analysis, statistical modeling, and visualization or experience with comparable programming languages and analytical tools.
- Demonstrated experience developing and evaluating machine learning or predictive models. Experience may come from biological research or other quantitative fields.
- Strong understanding of statistical analysis, predictive modeling, and interpretation of complex datasets.
- Experience with high-dimensional data analysis, preferably involving genomic or other biological datasets.
- Experience with Linux/Unix environments and computational workflows or similar operating systems and computational research platforms.
- Ability to critically evaluate analytical results and communicate findings clearly.
- Strong problem-solving skills, scientific curiosity, and interest in understanding biological mechanisms.
- Ability to work independently while collaborating effectively with an interdisciplinary research team.
Preferred Qualifications
- Master's degree or Ph.D. in biology, bioinformatics, computational biology, statistics, or a related field.
- Background in molecular biology, genetics, neuroscience, immunology, aging biology, or related disciplines.
- Experience analyzing bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, or epigenomic datasets.
- Familiarity with bioinformatics tools such as Seurat, Scanpy, DESeq2, or related packages.
- Experience using machine learning frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Experience with multi-omics integration, biomarker discovery, or biological classification models.
- Experience with reproducible computational workflows, version control, and high-performance computing.
- Experience contributing to biological research manuscripts or collaborative scientific projects.
OMRF Overview
Founded in 1946, the Oklahoma Medical Research Foundation (OMRF) is among the nation’s oldest, most respected independent, nonprofit biomedical research institutes. OMRF is dedicated to understanding and developing more effective treatments for human diseases, focusing on critical research areas such as Alzheimer’s disease, cancer, lupus, multiple sclerosis, and cardiovascular disease. OMRF follows an innovative cross-disciplinary approach to medical research and ranks among the nation’s leaders in patents per scientist.
Located in Oklahoma City, a city that offers a dynamic and flourishing downtown area, with low cost of living, short commute times and a diversified economy, OMRF has been voted one of the Top Workplaces since the inception of the award. This achievement has been accomplished thanks to OMRF individuals who share a unified understanding that our excellence can only be fully realized with a collective commitment to our mission, “. . . so that more may live longer, healthier lives.” Successful candidates will demonstrate commitment to this mission.
OMRF Benefits
We offer competitive salaries and comprehensive benefits to full-time employees including medical, dental, and vision insurance, minimum 8% company retirement contribution, vacation and sick leave, and paid holidays. All employees have access to our onsite café, free onsite fitness center with access to personal trainer, free parking and much more! Relocation assistance available for those located 50 miles outside of Oklahoma City metro. Learn more about our benefits here.
OMRF is an Equal Opportunity Employer.
Position Overview and Responsibilities
The Ocañas Lab is part of the Genes & Human Disease Research Program at OMRF, a nonprofit biomedical research institute in Oklahoma City. Our research investigates how biological sex, aging, and immune regulation influence neurodegenerative and other age-related diseases. Our laboratory combines cutting-edge genomic technologies, experimental biology, and computational approaches to understand how genetic, epigenetic, and environmental factors influence cellular function during aging. We are looking for an individual who enjoys working at the intersection of biology, statistics, and computational science. The ideal candidate will have strong analytical and programming skills, experience with machine learning and predictive modeling, and a genuine interest in understanding the biological questions underlying the data. The successful candidate will work closely with experimental scientists to develop analytical strategies, identify meaningful biological patterns, generate new hypotheses, and contribute to scientific discovery. We particularly value individuals who can think critically about biological mechanisms rather than simply apply established analytical pipelines.
Key Responsibilities:
Bioinformatics and Biological Data Analysis
- Analyze and interpret high-dimensional biological datasets, including bulk RNA-seq, single-cell/single-nucleus RNA-seq, spatial transcriptomics, and DNA methylation sequencing.
- Perform data quality control, normalization, differential expression analysis, pathway enrichment, cell-type characterization, and multi-omics integration.
- Investigate molecular mechanisms, regulatory networks, and cellular heterogeneity associated with aging and disease.
- Integrate genomic, epigenomic, imaging, and behavioral data to identify relationships across biological systems.
Machine Learning and Predictive Modeling
- Develop, evaluate, and interpret machine learning models to identify molecular signatures, classify biological states, and predict experimental or disease-related outcomes.
- Apply supervised and unsupervised approaches, including classification, regression, clustering, feature selection, and dimensionality reduction.
- Assess model performance using appropriate validation strategies, statistical methods, and measures of predictive accuracy.
- Identify biologically meaningful predictors and translate computational findings into testable hypotheses.
- Explore and implement emerging computational approaches for complex biological data analysis.
Scientific Collaboration and Computational Development
- Collaborate with laboratory members to formulate research questions, design analyses, and interpret experimental results.
- Apply statistical and computational approaches to experimental design, including sample size estimation and consideration of biological and technical variables.
- Develop and maintain reproducible analysis pipelines using R, Python, and high-performance computing resources.
- Generate scientific visualizations, figures, and analytical reports.
- Contribute to scientific manuscripts, grant applications, and research presentations.
- Provide computational guidance and training to other laboratory members.
- Stay current with emerging developments in bioinformatics, computational biology, and machine learning.
Minimum Qualifications
- Bachelor’s degree in Bioinformatics, Mathematics, Statistics, Computational Biology, Computer Science, or relevant field and 3 years of relevant experience/training or combination of education and experience.
- Proficiency in R and Python for data analysis, statistical modeling, and visualization or experience with comparable programming languages and analytical tools.
- Demonstrated experience developing and evaluating machine learning or predictive models. Experience may come from biological research or other quantitative fields.
- Strong understanding of statistical analysis, predictive modeling, and interpretation of complex datasets.
- Experience with high-dimensional data analysis, preferably involving genomic or other biological datasets.
- Experience with Linux/Unix environments and computational workflows or similar operating systems and computational research platforms.
- Ability to critically evaluate analytical results and communicate findings clearly.
- Strong problem-solving skills, scientific curiosity, and interest in understanding biological mechanisms.
- Ability to work independently while collaborating effectively with an interdisciplinary research team.
Preferred Qualifications
- Master's degree or Ph.D. in biology, bioinformatics, computational biology, statistics, or a related field.
- Background in molecular biology, genetics, neuroscience, immunology, aging biology, or related disciplines.
- Experience analyzing bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, or epigenomic datasets.
- Familiarity with bioinformatics tools such as Seurat, Scanpy, DESeq2, or related packages.
- Experience using machine learning frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Experience with multi-omics integration, biomarker discovery, or biological classification models.
- Experience with reproducible computational workflows, version control, and high-performance computing.
- Experience contributing to biological research manuscripts or collaborative scientific projects.
OMRF Overview
Founded in 1946, the Oklahoma Medical Research Foundation (OMRF) is among the nation’s oldest, most respected independent, nonprofit biomedical research institutes. OMRF is dedicated to understanding and developing more effective treatments for human diseases, focusing on critical research areas such as Alzheimer’s disease, cancer, lupus, multiple sclerosis, and cardiovascular disease. OMRF follows an innovative cross-disciplinary approach to medical research and ranks among the nation’s leaders in patents per scientist.
Located in Oklahoma City, a city that offers a dynamic and flourishing downtown area, with low cost of living, short commute times and a diversified economy, OMRF has been voted one of the Top Workplaces since the inception of the award. This achievement has been accomplished thanks to OMRF individuals who share a unified understanding that our excellence can only be fully realized with a collective commitment to our mission, “. . . so that more may live longer, healthier lives.” Successful candidates will demonstrate commitment to this mission.
OMRF Benefits
We offer competitive salaries and comprehensive benefits to full-time employees including medical, dental, and vision insurance, minimum 8% company retirement contribution, vacation and sick leave, and paid holidays. All employees have access to our onsite café, free onsite fitness center with access to personal trainer, free parking and much more! Relocation assistance available for those located 50 miles outside of Oklahoma City metro. Learn more about our benefits here.
OMRF is an Equal Opportunity Employer.
See all 33+ OPT Bioinformatics Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship in Bioinformatics
Target STEM-designated programs
Your bioinformatics degree likely qualifies for the 24-month STEM OPT extension. Confirm your program's CIP code with your DSO before job searching, so you can accurately communicate your full authorization window to employers.
Lead with your technical stack
Hiring managers in bioinformatics screen for tools like Python, R, Nextflow, and cloud platforms. Listing these prominently on your resume signals immediate productivity and reduces hesitation around OPT authorization timelines.
Focus on research-driven employers
Pharmaceutical companies, genomics firms, and academic medical centers file OPT and H-1B visa paperwork regularly. These organizations have established immigration processes, making them far more receptive to candidates on work authorization.
Quantify your research contributions
Employers respond to measurable impact. Frame your work around datasets processed, pipeline runtime improvements, or publications contributed to. Concrete outcomes shift the conversation away from visa status toward your value.
Apply before your OPT start date
Bioinformatics hiring processes at research institutions can run eight to twelve weeks. Starting your search three to four months before graduation gives you enough runway to have an offer in hand before OPT begins.
Clarify E-Verify requirements early
STEM OPT extension employers must be enrolled in E-Verify. Before investing time in an application, confirm the company meets this requirement, especially at smaller biotech startups where compliance processes are less established.
Bioinformatics OPT: Frequently Asked Questions
Do bioinformatics jobs qualify for the STEM OPT extension?
Most do. Bioinformatics, computational biology, and biostatistics degrees are commonly classified under STEM CIP codes that qualify for the 24-month STEM OPT extension. Your specific eligibility depends on your program's CIP code, not just the degree title, so verify with your DSO before assuming you qualify.
How do I find bioinformatics employers willing to sponsor OPT students?
Migrate Mate filters job listings specifically for employers open to OPT and visa sponsorship, which saves time compared to applying broadly and discovering authorization issues late in the process. Pharmaceutical companies, genomics research labs, and large hospital systems are the most consistent sources of OPT-friendly bioinformatics roles.
Can I work as a bioinformatics contractor or freelancer on OPT?
Self-employment is technically permitted on OPT if you own at least 50 percent of the business and the work is directly related to your degree. However, contract work for a single client without that structure may not qualify. STEM OPT extension specifically prohibits self-employment, so consult your DSO before pursuing contract arrangements.
What happens to my OPT if my bioinformatics job is remote for an employer based outside the U.S.?
OPT requires that the job be with a US-based employer. Working remotely for a company incorporated and operating outside the United States does not satisfy OPT employment requirements, even if you are physically located in the U.S.. The employer must have a legitimate U.S. presence and the work must be in your field of study.
Does part-time bioinformatics work count toward OPT employment requirements?
Yes, but with conditions. During pre-completion OPT you are limited to 20 hours per week while school is in session. During post-completion OPT you must work at least 20 hours per week to remain in valid status. Part-time bioinformatics roles at research institutions or biotech companies can satisfy this threshold.