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Internship Genomics Jobs in California (NOW HIRING)

Eurofins Scientific

Cell Culture Associate

San Diego, CA · On-site

$52K - $57K/yr

... genomics, discovery pharmacology, forensics, advanced material sciences and in the support of ... internship, or industry laboratory experience. * Hands-on experience with mammalian cell culture ...

Bio-Techne

Scientist, Probe Design

Newark, CA · On-site

$89K - $146K/yr

... genomic/epigenomic/transcriptomic) * Prior experience in probe design across multiple species ... internship programs, and more. * We offer employee resource groups, volunteer paid time off ...

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All JobsGenomics JobsInternship Genomics JobsInternship Genomics Jobs in California

Internship Genomics information

What types of projects or tasks are typically assigned to interns in genomics, and how do these contribute to real research outcomes?

Interns in genomics often participate in hands-on projects such as data analysis of sequencing results, assisting with laboratory experiments, or helping to maintain bioinformatics pipelines. These tasks are designed to support ongoing research projects and may involve collaboration with both computational and laboratory teams. Interns frequently contribute to the interpretation of genomic data, literature reviews, or even the development of new tools, which can have a real impact on the lab’s findings and publications. This exposure provides valuable experience and can lead to further opportunities in research or industry roles.

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

To thrive in a Genomics Internship, you typically need a background in biology, genetics, or related fields, along with foundational knowledge of molecular techniques and data analysis. Familiarity with bioinformatics tools, programming languages like Python or R, and next-generation sequencing platforms is often required. Strong analytical thinking, attention to detail, and effective communication help interns interpret data and collaborate with research teams. These skills are vital for supporting research projects, managing complex datasets, and contributing to scientific discoveries in genomics.

What is the difference between Internship Genomics vs Genomics Research Assistant?

AspectInternship GenomicsGenomics Research Assistant
Required CredentialsTypically students or recent graduates; some may have relevant courseworkUsually requires a bachelor's degree in biology, genetics, or related field
Work EnvironmentEducational settings, labs, internships at biotech companiesResearch labs, academic institutions, biotech companies
Employer & Industry UsageInternship programs, educational institutions, biotech firmsResearch institutions, universities, biotech companies
Common Search & Comparison IntentUnderstanding entry-level opportunities, learning rolesClarifying job responsibilities, career progression

Internship Genomics positions are typically entry-level, designed for students or recent graduates gaining practical experience. In contrast, Genomics Research Assistants are more established roles requiring a bachelor's degree and involve more independent research responsibilities. Both roles are common in research labs and biotech industries, but internships focus on learning, while research assistant roles emphasize contribution to ongoing projects.

What is an internship in genomics?

An Internship in Genomics is a temporary position, typically for students or recent graduates, that provides hands-on experience in the field of genomics. Interns may work in research laboratories, biotech companies, or healthcare institutions, assisting with projects related to DNA sequencing, genetic data analysis, or bioinformatics. The goal is to gain practical skills, learn from professionals, and build a foundation for a career in genomics. Internships can last from a few weeks to several months and may be paid or unpaid, depending on the organization. They are valuable for networking and exploring different career paths within the field.
What are the most commonly searched types of Genomics jobs in California? The most popular types of Genomics jobs in California are:
What are popular job titles related to Internship Genomics jobs in California? For Internship Genomics jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Genomics jobs in California look for? The top searched job categories for Internship Genomics jobs in California are:
What cities in California are hiring for Internship Genomics jobs? Cities in California with the most Internship Genomics job openings:
Internship Genomics jobs near you
Infographic showing various Internship Genomics job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 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