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Bioinformatics Engineer Jobs in Oregon (NOW HIRING)

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

POSITION SUMMARY: Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics,

UNAVAILABLE

Computational Biologist 1

Portland, OR · On-site

Department Overview The primary mission of the Division of Oncological Sciences at OHSU's Knight Cancer Institute is to better understand cancer through basic, translational and population-based

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All JobsBioinformatics Engineer JobsBioinformatics Engineer Jobs in Oregon

Bioinformatics Engineer information

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$45.5K

$138.6K

$252.2K

How much do bioinformatics engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for bioinformatics engineer in Oregon is $138,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $166,000.00 per year, depending on experience, location, and employer.

What is a bioinformatics engineer?

A Bioinformatics Engineer is a professional who combines expertise in computer science, statistics, and biology to develop software tools and algorithms for analyzing biological data. They often work with large datasets such as genomic sequences, protein structures, and clinical information to help scientists make sense of complex biological systems. Their work is essential in fields like genomics, personalized medicine, and drug discovery, where managing and interpreting vast amounts of data is crucial. Bioinformatics Engineers may also collaborate with researchers to design experiments and interpret results, bridging the gap between biology and technology.

What are the key skills and qualifications needed to thrive as a bioinformatics engineer?

To thrive as a Bioinformatics Engineer, you need a strong background in biology, computer science, and statistics, often supported by a degree in bioinformatics or a related field. Experience with programming languages such as Python or R, familiarity with databases, and knowledge of tools like BLAST, Bioconductor, or next-generation sequencing (NGS) analysis platforms are typically required. Strong problem-solving, analytical thinking, and effective communication skills help you collaborate with interdisciplinary teams and convey complex findings. These skills and qualifications are essential for efficiently analyzing biological data, developing robust computational tools, and advancing research in genomics and life sciences.

What are some common challenges faced by bioinformatics engineers when integrating new data sources into existing pipelines?

Bioinformatics Engineers often encounter challenges such as data format inconsistencies, varying quality of datasets, and the need to ensure compatibility with existing analysis pipelines. Integrating new data sources may require custom scripts or tools for parsing and preprocessing, as well as thorough validation to maintain reproducibility and reliability of results. Collaboration with wet-lab scientists and software engineers is essential to clarify data requirements and streamline the integration process.

What is the difference between Bioinformatics Engineer vs Bioinformatics Analyst?

AspectBioinformatics EngineerBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; programming skillsBachelor's or Master's in Bioinformatics, Biology, or related fields; data analysis skills
Work EnvironmentResearch labs, biotech companies, pharmaceutical firmsResearch institutions, healthcare organizations, biotech companies
Employer & Industry UsageDevelops tools, pipelines, and software for biological data analysisInterprets data, performs statistical analysis, and reports findings

While both roles require a background in bioinformatics and involve working with biological data, Bioinformatics Engineers focus on developing software and tools, whereas Bioinformatics Analysts primarily analyze and interpret data to support research and decision-making.

What does a bioinformatics engineer do?

A bioinformatics engineer develops and applies computational tools and algorithms to analyze biological data, such as genetic sequences and molecular structures. They often work with programming languages like Python or R, utilize databases, and collaborate with biologists to interpret data for research or medical purposes.
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Bioinformatics Engineer jobs near you
Infographic showing various Bioinformatics Engineer job openings in Oregon as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $138,560 per year, or $66.6 per hour.

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

Portland, OR • On-site

e184
See more jobs at e184external

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Key responsibilities

  • Lead computational analysis of multi-modal genomics data (scRNA-seq, ATAC-seq) to identify transcription factor combinations driving cell state conversion.

  • Collaborate with wet lab teams to translate computational predictions into experimental designs and update models based on new experimental data.

  • Rank transcription factor cocktails and decode pooled perturbation and CRISPRa screens at single-cell resolution to inform cellular reprogramming strategies.

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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