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Genomics Researcher Jobs in Oregon (NOW HIRING)

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Genomics Researcher information

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$31.7K

$119.6K

$173.9K

How much do genomics researcher jobs pay per year?

As of Aug 15, 2026, the average yearly pay for genomics researcher in Oregon is $119,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,800.00 and $162,800.00 per year, depending on experience, location, and employer.

What is a genomics researcher?

A Genomics Researcher is a scientist who studies the structure, function, evolution, and mapping of genomes, which are the complete sets of DNA within organisms. They conduct experiments and analyze genetic data to understand how genes influence health, disease, and biological processes. Genomics Researchers often work in academic, clinical, or private industry settings, contributing to advances in personalized medicine, biotechnology, and agriculture. Their work can lead to the development of new diagnostics, treatments, and preventive strategies for various genetic conditions.

What are some common challenges genomics researchers face when working on collaborative projects?

Genomics Researchers often collaborate with multidisciplinary teams, including bioinformaticians, clinicians, and statisticians. One common challenge is integrating and interpreting large, complex datasets from diverse sources, which requires strong communication and project management skills. Coordinating timelines, data sharing protocols, and aligning research goals can also be demanding. However, these collaborations offer valuable opportunities to learn from other experts and contribute to impactful discoveries.

What is the difference between Genomics Researcher vs Bioinformatics Analyst?

AspectGenomics ResearcherBioinformatics Analyst
Required CredentialsBachelor's or Master's in Genetics, Biology, or related field; PhD often preferredBachelor's or Master's in Bioinformatics, Computer Science, or related field; certifications beneficial
Work EnvironmentLaboratories, research institutions, universitiesComputing environments, research labs, biotech companies
Industry UsageAcademic research, biotech, healthcareData analysis, software development, research support

While both roles involve working with genetic data, Genomics Researchers focus on experimental design and laboratory work to understand genetic functions, whereas Bioinformatics Analysts primarily analyze genetic data using computational tools. Both roles are essential in genomics projects but differ in their core activities and skill sets.

What are the key skills and qualifications needed to thrive as a genomics researcher?

To thrive as a Genomics Researcher, you need a strong background in genetics, molecular biology, bioinformatics, and typically a graduate degree (MSc or PhD) in a related field. Proficiency with genomic sequencing platforms, data analysis software (such as Python, R, or specialized bioinformatics tools), and familiarity with laboratory information management systems (LIMS) are essential. Critical thinking, problem-solving, and effective collaboration skills help researchers design experiments, interpret data, and work in interdisciplinary teams. These competencies ensure rigorous scientific discovery, accurate data interpretation, and impactful research outcomes in the rapidly evolving field of genomics.

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

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

What job categories do people searching Genomics Researcher jobs in Oregon look for?

The top searched job categories for Genomics Researcher jobs in Oregon are:

What cities in Oregon are hiring for Genomics Researcher jobs?

Cities in Oregon with the most Genomics Researcher job openings:

Genomics Researcher jobs near you

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

About us
e184 Repro is a biotechnology research company with the mission of advancing in vitro gametogenesis to solve one of biology's most profound challenges: returning the fundamental right to procreate.
We work at the frontier of cutting-edge technology, integrating cellular reprogramming, machine learning-guided optimization, multi-omics analysis, and automated experimental workflows to enable gamete development for individuals facing reproductive challenges.
Role overview
As a Bioinformatics Scientist with a cellular reprogramming background, you will lead computational analysis of multi-modal genomics data (scRNA-seq, ATAC-seq) to identify transcription factor combinations driving desired cell state conversion. This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring deep expertise in multi-platform scRNA-seq analysis and transcriptional regulation biology. You will collaborate closely with wet lab teams to translate computational predictions into experimental designs, while also exploring hybrid approaches that integrate foundation model insights into our reprogramming pipeline.
What you'll do
  • Lead end-to-end TF discovery for cellular reprogramming - from multi-platform single-cell genomics analysis (scRNA-seq, ATAC-seq) through GRN inference, differential analysis, and trajectory mapping - to nominate the regulators that flip cell fate.
  • Crack the combinatorial code of reprogramming by ranking TF cocktails as actionable combinations and decoding pooled perturbation and CRISPRa screens at single-cell resolution.
  • Read regulatory grammar straight off the chromatin - accessibility, motifs, synergy, repression - and build the data backbone that harmonizes modalities and platforms into something we can actually model on.
  • Sit shoulder-to-shoulder with wet lab teammates, closing the loop between predictions and screens: ingest fresh NGS readouts, retrain, re-prioritize, and pick the next experiment that teaches the model the most.

Core requirements
  • PhD in Bioinformatics, Computational Biology, or related quantitative field (or MS with 5+ years relevant industry experience);
  • Demonstrated track record applying computational TF ranking and GRN inference to cellular reprogramming problems, transdifferentiation, directed differentiation, or iPSC systems;
  • Multi-platform single-cell RNA-seq expertise: hands-on analysis from at least two different platforms, including platform-specific troubleshooting and quality control;
  • Multi-modal genomics proficiency: ChIP-seq, CUT&RUN, or ATAC-seq analysis including peak calling, differential accessibility, and TF motif enrichment;
  • Hands-on experience with established GRN inference methods to nominate or rank regulators of cell state, beyond literature-curated lists;
  • Experience analyzing pooled perturbation screens (CRISPRa, CRISPR knockout, or barcoded TF overexpression) with single-cell or bulk readouts;
  • Working knowledge of trajectory inference and pseudotime methods for mapping cell state transitions;
  • Strong programming skills in Python and R, with proficiency in Scanpy/Seurat and statistical analysis for high-dimensional data;
  • Comfortable working in a modern computational environment: cloud platforms, workflow managers, containerization, and collaborative version control;
  • Strong publication record and demonstrated cross-functional collaboration with experimental biologists.

You'll stand out with
  • Direct experience nominating or validating TF cocktails that successfully induced a cell state conversion (published or in preparation).
  • Experience with dynamical systems modeling for cell state transitions, or inverse problem approaches for TF combination ranking.
  • Background in advanced trajectory inference (optimal transport, GRN dynamics over pseudotime), Bayesian genomics, multi-omics integration, or cross-species comparative regulatory genomics.
  • Familiarity with transformer architectures in genomics and interest in hybrid classical/ML approaches to gene regulation.

Why e184?
  • Unrivaled impact: Your work directly enables technology that transforms human fertility and reproductive medicine.
  • Full-spectrum growth: Gain exposure to the entire lifecycle of discovery. From screening to mechanistic validation.
  • Best of both worlds: Experience the creative chaos of an early-stage startup with the stability of a well-capitalized company.
  • Elite collaboration: Work alongside a world-class team who are as driven as you are.

What we offer
  • Competitive salary + equity participation is considered
  • State-of-the-art facility in Portland metro area
  • Comprehensive Medical, Dental, Vision, and 401(k) with company match
  • 20 days PTO + 11 paid holidays

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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