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Internship Plant Bioinformatics Jobs (NOW HIRING)

New York Botanical Garden

Science Intern

New York, NY · On-site

$17/hr

The Science Internship is a part-time and seasonal position that provides training opportunities ... Research areas may include but are not limited to plant diversity, museum curation, molecular ...

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Internship Plant Bioinformatics information

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How much do internship plant bioinformatics jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for internship plant bioinformatics in the United States is $19.25, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.39 per hour, depending on experience, location, and employer.

What is an internship in plant bioinformatics?

An Internship in Plant Bioinformatics is a temporary, hands-on position where students or recent graduates work on projects that apply computational and statistical techniques to analyze biological data related to plants. Interns may assist with research on plant genomes, gene expression, or molecular pathways using bioinformatics tools and software. This experience provides practical knowledge in both biology and computer science, preparing interns for careers in research, biotechnology, or academia. Interns often work alongside scientists and contribute to real-world projects that can impact agriculture, conservation, and plant breeding.

What kinds of projects or tasks can I expect to work on during a plant bioinformatics internship?

As a Plant Bioinformatics intern, you will likely assist with analyzing large sets of plant genomic or transcriptomic data, using bioinformatics tools to interpret results, and supporting research on gene expression or plant trait improvement. Interns often contribute to data cleaning, running computational pipelines, and documenting results for ongoing projects. You may also collaborate with molecular biologists, data scientists, and other interns, gaining exposure to interdisciplinary teamwork and the research process within an academic or industry lab setting.

What are the key skills and qualifications needed to thrive as an internship plant bioinformatics, and why are they important?

To succeed as an Internship Plant Bioinformatics, you generally need a background in biology, genetics, or bioinformatics, supported by coursework or experience in computational biology. Familiarity with programming languages such as Python or R, knowledge of bioinformatics databases, and experience using tools like BLAST or genome analysis pipelines are often required. Strong analytical thinking, problem-solving abilities, and effective communication skills help interns interpret complex data and collaborate with research teams. These competencies are crucial for accurately analyzing plant genomic data and contributing valuable insights to research projects.

What is the difference between Internship Plant Bioinformatics vs Plant Biotechnologist?

AspectInternship Plant BioinformaticsPlant Biotechnologist
Required CredentialsEnrolled in or recent graduate of relevant degree (Bioinformatics, Biology)Degree in Biology, Biotechnology, or related field; often advanced degrees
Work EnvironmentResearch labs, academic institutions, biotech companies, primarily data analysisLaboratories, fieldwork, research facilities, product development
Industry UsageData analysis, computational research, supporting plant science projectsDeveloping genetically modified plants, improving crop traits

Internship Plant Bioinformatics focuses on data analysis and computational skills within plant science, often as a temporary position for students or recent graduates. In contrast, Plant Biotechnologists are involved in hands-on laboratory work and developing new plant varieties, typically requiring more advanced credentials and experience. Both roles are essential in plant research but differ in scope, environment, and career progression.

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Internship Plant Bioinformatics jobs near you
Infographic showing various Internship Plant Bioinformatics job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 6% Part Time, 2% Contract, and 3% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $40,032 per year, or $19.2 per hour.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago

Job description


JOB SUMMARY

The Biostatistics Scientist supports applied statistical analysis, quantitative genetics, and breeding analytics for vegetable crop research programs. This entry-level role contributes to genomic, phenotypic, and field-trial data analysis under the guidance of senior scientists, managers and cross-functional project teams. The position helps develop reliable, reproducible analytical workflows that improve trait evaluation, marker-assisted selection, genomic prediction, and data-driven breeding decisions.

Key Responsibilities

Statistical Analysis, Quantitative Genetics & Genomic Prediction

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.
  • Apply standard statistical and quantitative genetics methods, such as mixed models, heritability estimation, genetic correlations, and basic genomic prediction approaches.
  • Assist with evaluating model performance, prediction accuracy, and data quality across populations, environments, and breeding stages.
  • Contribute to analyses that help breeders understand trait variation, experimental results, and selection opportunities.
  • Document methods, assumptions, code, and results clearly to support reproducibility and team review.

Molecular Marker & Trait Analytics

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.
  • Assist molecular and breeding teams with data summaries for marker development, marker deployment, and trait evaluation projects.
  • Support quality control of genotypic and phenotypic datasets, including data cleaning, formatting, consistency checks, and basic exploratory analysis.
  • Help prepare selection metrics, trait summaries, and visualizations that integrate multiple sources of breeding data.
  • Translate analytical results into concise summaries that can be reviewed by breeders, molecular scientists, and project teams.

Genomic, Phenotypic & Field Trial Data Analysis

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.
  • Develop and maintain reproducible scripts for data quality control, statistical analysis, visualization, and reporting.
  • Contribute to the improvement of analytical templates, reporting workflows, and shared data practices in collaboration with bioinformatics and data teams.

Project Support & Cross-Functional Collaboration

  • Support analytical components of breeding, trait development, molecular marker, and technology projects.
  • Collaborate with breeders, phenotyping, molecular biology, bioinformatics, and data teams to understand project objectives and data requirements.
  • Prepare clear technical summaries, tables, figures, and presentations to communicate results to internal stakeholders.
  • Learn and apply current methods in biostatistics, quantitative genetics, breeding analytics, and reproducible scientific computing.


Required Qualifications

Education

  • PhD in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field; industry experience a plus
    or
  • MS in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field with 0–2 years of relevant academic, internship; industry experience a plus


Experience & Technical Skills

  • Foundational training in statistics, biostatistics, quantitative genetics, plant breeding, computational biology, or related analytical disciplines.
  • Experience with statistical analysis of biological, genomic, phenotypic, field-trial, or experimental datasets through graduate research, internships, or applied projects.
  • Working knowledge of statistical programming in R, Python, SAS, or similar tools.
  • Good understanding of experimental design, mixed models, regression, data visualization, and reproducible analytical workflows.
  • Experience with molecular markers, genomic data, plant breeding concepts, or trait analysis is desirable.
  • Ability to learn new methods, manage multiple analytical tasks, and deliver accurate results with guidance.
  • Strong attention to detail, scientific curiosity, communication skills, and willingness to collaborate across disciplines.

Preferred Qualifications

  • Research experience in plant breeding, seed industry research, agricultural biotechnology, or applied life-science data analysis.
  • Experience in genomic prediction, QTL mapping, GWAS, marker-assisted selection, or trait discovery workflows.
  • Familiarity with breeding databases, phenotyping systems, laboratory information systems, or integrated data platforms.
  • Experience preparing figures, tables, dashboards, or technical reports for scientific or cross-functional audiences.
  • Exposure to cloud-based, Linux, Git, or high-performance computing environments for data analysis.
  • Interest in applying AI, machine learning, and modern statistical methods to practical breeding and research questions.

Competencies & Behaviors

  • Demonstrates curiosity, initiative, and accountability in learning new analytical methods and scientific workflows.
  • Applies statistical methods carefully, with attention to data quality, assumptions, and reproducibility.
  • Works collaboratively with scientists from breeding, molecular biology, phenotyping, bioinformatics, and data teams.
  • Communicates analytical results clearly to both technical and non-technical audiences.
  • Manages assigned tasks effectively, asks timely questions, and follows through on deliverables.
  • Contributes to a culture of scientific rigor, continuous improvement, teamwork, and practical problem solving.

Reporting Structure

  • Reports to Senior Biotech Manager

Works under the guidance of senior scientists, project leads, and cross-functional research teams

BENEFITS:

Health & Wellness
Medical, Dental & Vision Insurance
Monthly Wellness Stipend
Employee Assistance Program (EAP)

Employee Philanthropic Giving Program

Disability Insurance (plans vary by location)


Financial Benefits
401(k) Program + Company Match
Profit Sharing Program (via 401(k)

Holiday Bonus

Performance Incentive Bonus Program
Tuition Reimbursement

529 College‑Savings Plan
Company-Paid Basic Life & AD&D Insurance


Time Off & Flexibility
Paid Vacation
Paid Sick Leave
15 Paid Company Holidays
2 Floating Holidays

Birthday Off