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Genomics Jobs in Oregon (NOW HIRING)

Build and define the Bioinformatics function within the Data Science development team, identify technical tooling gaps, and execute a roadmap to advance genomics-based algorithm development.

New

Student Worker

Portland, OR · On-site

$14.75 - $16.75/hr

Department OverviewThe O'Roak lab is focused on using genomic approaches to unlock the genetic basis of neurodevelopmental disorders and related disorders, such as autism and intellectual disability.

Student Worker

Portland, OR · On-site

$14.75 - $16.75/hr

Department OverviewThe O'Roak lab is focused on using genomic approaches to unlock the genetic basis of neurodevelopmental disorders and related disorders, such as autism and intellectual disability.

Student Worker

Portland, OR · On-site

$14.75 - $16.75/hr

Department OverviewThe O'Roak lab is focused on using genomic approaches to unlock the genetic basis of neurodevelopmental disorders and related disorders, such as autism and intellectual disability.

Showing results 21-40

Genomics information

See Oregon salary details

$34.9K

$117.2K

$194K

How much do genomics jobs pay per year?

As of Aug 16, 2026, the average yearly pay for genomics in Oregon is $117,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,831.00 and $153,102.00 per year, depending on experience, location, and employer.

What jobs can you get with a genomics degree?

A genomics degree can lead to roles such as genomic researcher, bioinformatics analyst, laboratory technician, or clinical geneticist. These jobs often require skills in molecular biology, data analysis, and familiarity with sequencing technologies and software tools.

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

To thrive in a Genomics role, you need a strong background in molecular biology, genetics, and bioinformatics, typically supported by an advanced degree in a life science and relevant laboratory experience. Proficiency with genomic sequencing platforms (such as Illumina or Oxford Nanopore), data analysis software, and experience with databases like NCBI or Ensembl are commonly required. Critical thinking, attention to detail, and collaborative communication are essential soft skills for interpreting complex data and working within multidisciplinary teams. These competencies are important for ensuring accurate genetic analysis, driving research projects, and making meaningful scientific contributions.

What is a genomics job?

A genomics job involves studying an organism's entire genetic makeup to understand gene functions, interactions, and variations. Professionals in this field work in research, healthcare, pharmaceuticals, or biotechnology, using advanced tools like sequencing technologies and bioinformatics. Their work can help in disease research, precision medicine, agriculture, and evolutionary biology. Common roles include genomic scientists, bioinformaticians, and clinical geneticists.

What are typical daily responsibilities for someone working in genomics?

Professionals in Genomics typically spend their days designing experiments, preparing and processing biological samples, and conducting analyses using high-throughput sequencing technologies. They also interpret large datasets using specialized bioinformatics tools, prepare reports or present findings to stakeholders, and collaborate with other scientists such as clinicians, computational biologists, or data analysts. The work environment can be a mix of laboratory work and computational data analysis, depending on the specific position. Regular team meetings and collaboration are common, especially in research or clinical settings where interdisciplinary problem-solving is essential.

Is genomics a good career?

Genomics is a growing field that involves studying an organism's complete set of DNA. Careers in genomics often require strong skills in molecular biology, bioinformatics, and laboratory techniques, with opportunities in research, healthcare, and biotechnology sectors. The field offers competitive salaries and demand for skilled professionals is expected to increase with advances in personalized medicine and genetic research.

Does genomics pay well?

Genomics professionals, such as genomic scientists and bioinformaticians, typically earn competitive salaries that vary based on experience, education, and location. Entry-level positions may start lower, but experienced roles with advanced skills in sequencing technologies and data analysis can command high salaries, especially in research institutions and biotech companies.

What are the most commonly searched types of Genomics jobs in Oregon?

The most popular types of Genomics jobs in Oregon are:

What are popular job titles related to Genomics jobs in Oregon?

For Genomics jobs in Oregon, the most frequently searched job titles are:

What cities in Oregon are hiring for Genomics jobs?

Cities in Oregon with the most Genomics job openings:

Infographic showing various Genomics job openings in Oregon as of August 2026, with employment types broken down into 88% Full Time, 7% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $117,158 per year, or $56.3 per hour.

Lead Bioinformatician (cfDNA Algorithms and Pipelines)

Natera

OR • On-site, Remote

Full-time

Posted 5 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

56th of 120 rated laboratories


Job description

Natera is seeking a Lead Bioinformatician to advance the algorithmic foundations of our diagnostic assays supporting Women's and Organ health. This is an individual contributor role. You will bring the genomics expertise the team needs to pull reliable signals out of sequencing data that is often ambiguous.

You will build the methodological foundations and implement the algorithms needed for detecting variants (SNVs, Indels, CNVs, SVs) that are hard to call accurately in low fraction (fetal, donor cfDNA) samples. The ideal candidate will have deep experience in algorithmic genomics, strong programming skills, and a passion for developing scalable, clinically impactful computational tools.

Primary Responsibilities:

Panel and Assay Science: Provide genomics algorithm insights to our expanded panel roadmap, including which genes are worth considering and why, working with Product, the Laboratory Directors, and Research, who own that decision jointly. Help define the approach for analytically difficult genes and assay edge cases, and weigh what is scientifically defensible against what is technically possible.

Caller Strategy and Method Development: Define the computational strategy for new targeted and special-purpose callers. Help decide when a new caller is justified and when an existing method should be extended instead. Prototype and benchmark new methods, and work with the engineering team to get methods into production.

Scientific Investigation and Escalation: Serve as a genomics consultant on complex production escalations, separating biological causes from analytical and pipeline ones. Recognize when a result looks suspicious because of where the reads came from and not because the analysis went wrong. Turn one-off investigations into durable rules and design changes that reduce repeat work.

Data Quality and Cross-functional Partnership: Act as bioinformatics liaison with Variant Management, Reporting, and Laboratory Operations on data quality, variant representation, and system integration. Provide the scientific rationale that the accountable Quality and Laboratory functions rely on when they decide a method is ready to deploy.

Ways of Working: Help define what correct looks like for AI-assisted scientific investigation, for example what an agent may and may not conclude from a region-level finding without a human signing off. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide the tooling and the ramp time.

What success looks like after a year:
  • Contributed to the scientific and bioinformatics rationale of product roadmaps.
  • Deployment-readiness criteria for new analysis methods exist and are in use, and you have contributed to at least one new or extended caller yourself.
  • You take on the bioinformatics aspects inside complex production investigations without waiting to be assigned them.
  • Other groups know they can bring genomics questions about our assays to you.
Qualifications:
  • Degree in Bioinformatics, Computational Biology, Bioinformatics, Human Genetics, or a related field. We do not require a Ph.D. or M.S.: equivalent depth built through work counts fully.
  • 4+ years analyzing short-read sequencing data for screening or diagnostic applications, preferably in a regulated, accredited, or production-adjacent setting. We count relevant experience from the point your work became substantially independent, however you got there.
  • Experience contributing to the bioinformatics workflows behind a sequencing assay or panel.
  • Experience seeing a complex investigation through to resolution across biological, analytical, and systems-level causes.
Knowledge, Skills, and Abilities:What we are screening for
  • Experience developing, validating, or benchmarking bioinformatics methods (e.g. SNVs, CNVs, SVs), particularly for analytically difficult regions.
  • Proficient in Python with demonstrated experience prototyping bioinformatics tools or callers.
  • Enough human genetics depth to contribute to the panel design: variant spectrum, population frequency, and where compromises on accuracy can (and cannot) be made.
  • Familiarity with identifying regions where short reads cannot be placed with confidence: homologous sequence and pseudogenes, low-complexity and repeat structure, and copy-number-heavy regions.
  • Experience contributing to study designs or performance criteria for a bioinformatics analysis method.
Strong candidates may also have
  • Direct non-invasive prenatal, reproductive, or carrier screening experience.
  • Experience with cfDNA, or with another application where the molecules you care about are a small minority of what was sequenced.
  • Experience developing algorithms for both short-read and long-read sequencing platforms (e.g., Illumina, ONT, PacBio).
  • Cross-functional credibility with genetic counseling, variant management, reporting, and production-adjacent groups.
  • Experience in an accredited or high-complexity laboratory, or familiarity with production support or escalation processes.

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