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Bioinformatics Phd information

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$99.9K

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How much do bioinformatics phd jobs pay per year?

As of Sep 7, 2026, the average yearly pay for bioinformatics phd in Oregon is $99,886.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,400.00 and $136,900.00 per year, depending on experience, location, and employer.

What is a bioinformatics PhD?

A Bioinformatics PhD job involves conducting research and developing computational tools to analyze biological data, such as genomics, proteomics, and clinical datasets. Professionals in this role work at the intersection of biology, computer science, and mathematics to derive meaningful insights from complex biological information. They may work in academia, pharmaceutical companies, biotechnology firms, or healthcare institutions, contributing to advancements in medicine, drug discovery, and personalized healthcare. Essential skills include programming, statistical analysis, machine learning, and a deep understanding of molecular biology.

What does a bioinformatics PhD do?

In a Bioinformatics PhD role, you may be tasked with designing and implementing computational analyses to interpret large-scale genomic or proteomic data, developing new algorithms or pipelines, and contributing to manuscripts or research publications. Collaboration with experimental biologists, clinicians, and fellow data scientists is common, requiring you to translate complex biological questions into computational approaches and communicate results effectively. On a daily basis, you might analyze sequencing data, troubleshoot code, manage data workflows, and help mentor junior researchers or students. These responsibilities offer dynamic opportunities to make a significant impact in advancing biological research and medical innovation.

What skills and qualifications are needed for a bioinformatics PhD?

A successful Bioinformatics PhD possesses advanced knowledge in computational biology, statistics, genomics, and a doctoral degree in bioinformatics or a closely related field. Familiarity with programming languages such as Python or R, experience with bioinformatics databases, and use of tools like BLAST, Galaxy, or Bioconductor are commonly expected. Strong analytical thinking, effective communication, and collaborative skills are highly valued in this field. These skills enable bioinformatics professionals to analyze complex biological data, work efficiently within multidisciplinary teams, and drive meaningful scientific discoveries.

What are popular job titles related to Bioinformatics Phd jobs in Oregon?

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

What job categories do people searching Bioinformatics Phd jobs in Oregon look for?

The top searched job categories for Bioinformatics Phd jobs in Oregon are:

Bioinformatics Phd jobs near you
Infographic showing various Bioinformatics Phd job openings in Oregon as of August 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $99,886 per year, or $48 per hour.

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 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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