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Phd In Genetics Jobs in California (NOW HIRING)

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Phd In Genetics information

What is the difference between Phd In Genetics vs Genetic Counselor?

AspectPhd In GeneticsGenetic Counselor
Required CredentialsPhD in Genetics or related fieldMaster's in Genetic Counseling, certification (ABGC)
Work EnvironmentResearch labs, academia, biotech companiesHospitals, clinics, healthcare settings
Industry UsageResearch, academia, biotech industryHealthcare, patient counseling

While a Phd In Genetics focuses on research, experimentation, and advancing genetic knowledge, a Genetic Counselor primarily provides patient support, risk assessment, and genetic testing guidance. Both roles require understanding genetics but serve different professional and industry needs.

Can I be a geneticist with a PhD?

Yes, a PhD in Genetics is typically required to become a geneticist, especially for research, academic, or specialized roles. Additional skills such as laboratory techniques, data analysis, and knowledge of genetic tools are also important for success in the field.

What can I do with a PhD in genetics?

A PhD in genetics prepares individuals for research roles in academia, biotechnology, pharmaceuticals, and healthcare, where they analyze genetic data, develop new technologies, or study genetic diseases. Graduates often work as research scientists, genetic counselors, or in regulatory and policy positions, utilizing skills in laboratory techniques, data analysis, and scientific communication.

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Phd In Genetics jobs near you
Infographic showing various Phd In Genetics job openings in California as of August 2026, with employment types broken down into 2% As Needed, 78% Full Time, 17% Part Time, 2% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Bioinformatics Engineer - Variant

Jobtailor

San Francisco, CA • On-site

$150 - $210/hr

Other

Posted 5 days ago

Job description

  • You’ll design, build, and evaluate LLM benchmarks for genomic analysis - spanning read alignment, assembly, variant calling, GWAS, causal inference, and multiomics integration.
  • Your benchmarks and evaluations will set the bar for how well AI agents can serve as analysis partners for scientists working with human genetics data.
  • You’ll own the full evaluation pipeline: choosing datasets, defining failure modes, writing grading scripts, and shipping evaluations that measure real capability.
  • Your work directly impacts how LLMs reason through genomic problems.
Requirements
  • Master's or PhD in bioinformatics, genetics, biology, statistics, or related field
  • 3-5 years of hands-on research experience analyzing genomics datasets (especially human data), demonstrated through publications or industry work
  • Deep expertise in at least one of: population genetics, statistical genetics, clinical genomics
  • Fluency with genotyping workflows: variant calling, fine-mapping, Mendelian randomization
Core Competencies

Demonstrates expertise in designing and evaluating LLM benchmarks for genomic analysis, with a strong focus on human genetics data and proficiency in genotyping workflows. Capable of managing the full evaluation pipeline, including dataset selection and performance measurement.

Highest-signal resume keywords
  • Master's Or PhD In Bioinformatics
  • 3-5 Years Research Experience In Genomics
  • Deep Expertise In Population Genetics
  • Fluency With Genotyping Workflows
  • Experience With Variant Calling
ATS Optimization Keywords Hard Skills
  • Genomic Analysis
  • Read Alignment
  • Assembly
  • Variant Calling
  • GWAS
  • Causal Inference
  • Multiomics Integration
  • Statistical Genetics
  • Clinical Genomics
Industry Keywords
  • Human Genetics Data
  • Evaluation Pipeline
  • Datasets
  • Failure Modes
  • Grading Scripts
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