This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring ...
This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring ...
This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring ...
This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
Research Associate
Portland, OR · On-site
$50.81K - $84.70K/yr
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
Research Associate
Portland, OR · On-site
$50.81K - $84.70K/yr
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
... spatial, single-cell, and bulk RNA libraries for sequencing, cell culture, and flow cytometry. The Research Associate will also be responsible for contributing to documentation and data analysis ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Postdoctoral Scholar
Portland, OR · On-site
$66.93K - $81.28K/yr
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Postdoctoral Scholar
Portland, OR · On-site
$66.93K - $81.28K/yr
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Our lab integrates spatial proteomics, single-cell transcriptomics, and epigenomics , and advanced 3D ex vivo and in vivo mouse models to dissect neural regulation of cancer. We are specifically ...
Assistant Staff Scientist
Portland, OR · On-site
$68.31K - $113.84K/yr
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
Assistant Staff Scientist
Portland, OR · On-site
$68.31K - $113.84K/yr
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
Assistant Staff Scientist
Portland, OR · On-site
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
Assistant Staff Scientist
Portland, OR · On-site
The work we do spans traditional materials science and cell biology. We'd love for you to join us ... Familiarity with spatial analysis approaches such as spatial transcriptomics, especially for ...
Senior Scientist - Placenta Biology
Portland, OR · On-site
$97K - $132.60K/yr
Experience with transcriptomic, single-cell, or spatial omics approaches in developmental systems > * Familiarity with perfusion or microphysiological culture platforms > * Experience translating in ...
Senior Scientist - Placenta Biology
Portland, OR · On-site
$97K - $132.60K/yr
Experience with transcriptomic, single-cell, or spatial omics approaches in developmental systems > * Familiarity with perfusion or microphysiological culture platforms > * Experience translating in ...
Senior Scientist - Placenta Biology
$97K - $132.60K/yr
Experience with transcriptomic, single-cell, or spatial omics approaches in developmental systems * Familiarity with perfusion or microphysiological culture platforms * Experience translating in vivo ...
Senior Scientist - Placenta Biology
$97K - $132.60K/yr
Experience with transcriptomic, single-cell, or spatial omics approaches in developmental systems * Familiarity with perfusion or microphysiological culture platforms * Experience translating in vivo ...
Single Cell Spatial Transcriptomics information
See Portland, OR salary details
$13.51 - $15.18
3% of jobs
$15.18 - $16.85
6% of jobs
$17.79 is the 25th percentile. Wages below this are outliers.
$16.85 - $18.52
27% of jobs
The median wage is $20.01 / hr.
$18.52 - $20.19
15% of jobs
$20.19 - $21.85
9% of jobs
$21.85 - $23.52
0% of jobs
$23.52 - $25.19
1% of jobs
$25.19 - $26.86
6% of jobs
$28.02 is the 75th percentile. Wages above this are outliers.
$26.86 - $28.53
9% of jobs
$28.53 - $30.20
9% of jobs
$30.20 - $31.87
13% of jobs
$13
$22
$31
How much do single cell spatial transcriptomics jobs pay per hour?
As of May 31, 2026, the average hourly pay for single cell spatial transcriptomics 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 the key skills and qualifications needed to thrive as a Single Cell Spatial Transcriptomics Scientist, and why are they important?
To thrive as a Single Cell Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree (PhD or MSc) in a relevant field. Familiarity with high-throughput sequencing platforms, spatial transcriptomics technologies (like 10x Genomics Visium or NanoString GeoMx), and data analysis tools such as R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These skills and qualities are vital for generating reliable insights into cellular function and spatial organization, which drive innovative research and discovery.
What are some typical challenges faced by professionals working in Single Cell Spatial Transcriptomics, and how can they be addressed?
Professionals in Single Cell Spatial Transcriptomics often encounter challenges related to handling large, complex data sets and integrating spatial information with single-cell transcriptomic profiles. These tasks demand strong computational skills and close collaboration with bioinformaticians and other researchers. Effective communication within interdisciplinary teams is essential to ensure experimental design aligns with downstream analysis needs. Staying updated with rapidly evolving technologies and best practices also helps professionals overcome technical hurdles and produce reliable, high-impact results.
What is single cell spatial transcriptomics?
Single cell spatial transcriptomics is a cutting-edge technique that allows researchers to analyze gene expression in individual cells while preserving their spatial location within a tissue. This method combines the high-resolution insights of single-cell RNA sequencing with spatial information, enabling scientists to understand how cells interact and organize within their native environments. It is widely used in biomedical research to study tissue architecture, disease mechanisms, and cellular heterogeneity.
What are popular job titles related to Single Cell Spatial Transcriptomics jobs in Portland, OR? For Single Cell Spatial Transcriptomics jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Single Cell Spatial Transcriptomics jobs in Portland, OR look for? The top searched job categories for Single Cell Spatial Transcriptomics jobs in Portland, OR are:
What cities near Portland, OR are hiring for Single Cell Spatial Transcriptomics jobs? Cities near Portland, OR with the most Single Cell Spatial Transcriptomics job openings:
Full-time
Medical, Dental, Vision, Retirement, PTO
Posted 5 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
Core requirements
You'll stand out with
Why e184?
What we offer
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.
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. 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.