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Single Cell Rna Sequencing information

See Portland, OR salary details

$13

$22

$31

How much do single cell rna sequencing jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for single cell rna sequencing in Portland, OR is $22.95, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $28.80 per hour, depending on experience, location, and employer.

What are some common challenges faced by researchers working in Single Cell RNA Sequencing, and how can they be addressed?

Researchers in Single Cell RNA Sequencing often encounter challenges such as sample preparation variability, data complexity, and managing large datasets. Ensuring high-quality single-cell suspensions and minimizing cell loss during processing are critical steps. Additionally, interpreting data requires proficiency with bioinformatics tools and collaboration with computational biologists. Staying up-to-date with evolving protocols and leveraging multi-disciplinary teamwork can help address these challenges effectively.

What is the difference between Single Cell Rna Sequencing vs Single Cell Genomics Technician?

AspectSingle Cell Rna SequencingSingle Cell Genomics Technician
CredentialsTypically requires a degree in biology, molecular biology, or related fields; experience with sequencing technologiesSimilar credentials; often with laboratory or technical certifications in genomics
Work EnvironmentLaboratories performing sequencing, data analysis, and sample preparationLaboratories focused on sample processing, sequencing support, and data collection
Industry UsageUsed in research labs, biotech, and pharmaceutical companies for gene expression studiesCommon in genomics research centers, biotech firms, and academic labs

Both roles involve working with genomic technologies and require similar educational backgrounds. However, Single Cell Rna Sequencing specialists focus more on RNA analysis and data interpretation, while Single Cell Genomics Technicians support sample preparation and sequencing workflows. Understanding these differences helps in choosing the right career path or job search focus.

What are the key skills and qualifications needed to thrive as a Single Cell RNA Sequencing Specialist, and why are they important?

To thrive as a Single Cell RNA Sequencing Specialist, you need a solid background in molecular biology, genomics, and data analysis, typically supported by a relevant degree in the life sciences. Familiarity with sequencing platforms (such as 10x Genomics or Illumina), bioinformatics tools (like Seurat or Cell Ranger), and experience with data visualization are crucial. Attention to detail, problem-solving ability, and strong communication skills help ensure accurate results and effective collaboration with research teams. Mastering these skills is essential for generating high-quality data, troubleshooting experiments, and translating complex findings into actionable insights.

What is single cell RNA sequencing?

Single cell RNA sequencing (scRNA-seq) is a technique that allows researchers to examine the gene expression profiles of individual cells. Unlike traditional RNA sequencing, which measures average gene expression across thousands or millions of cells, scRNA-seq reveals the unique transcriptomic signature of each cell. This method is valuable for studying cellular diversity, identifying rare cell types, and understanding complex biological processes such as development, disease progression, and immune responses.
What are popular job titles related to Single Cell Rna Sequencing jobs in Portland, OR? For Single Cell Rna Sequencing jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Single Cell Rna Sequencing jobs in Portland, OR look for? The top searched job categories for Single Cell Rna Sequencing jobs in Portland, OR are:
Single Cell Rna Sequencing jobs near you

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 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 youll 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.

Youll 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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