Research Scientist/Engineer I (RSE1) — Spatial Bioinformatics

We are hiring an early‑career bioinformatician/data scientist to build and operate robust, reproducible pipelines for Pixel‑seq and ImmunoPixel‑seq. You will help transform raw sequencing and imaging outputs into high‑quality, spatially resolved single‑cell datasets used across projects in brain, tumor, aging, and immunology.

Applications are reviewed on a rolling basis.

Priority review begins: January 1, 2026 (open until filled).

About the Gu Lab

The Gu Lab at the University of Washington develops and applies next‑generation spatial omics technologies to address important questions in neuroscience, cancer, aging, and immunology. We integrate array fabrication, sequencing, imaging, and computation to generate spatially resolved, single‑cell–scale datasets and convert them into biological insights.

The role

This is a staff Research Scientist/Engineer (RSE1) position focused on computational pipeline development and data analysis. You will work closely with Dr. Liangcai Gu, lab members, and collaborators to process Pixel‑seq / ImmunoPixel‑seq data, maintain a reliable analysis workflow, and deliver interpretable results for ongoing funded research.

This role is ideal for a strong CS/math/computational graduate (or equivalent experience) who enjoys writing clean code and wants real scientific impact (including opportunities for co‑authorship depending on contributions). It is also a great fit for applicants considering future MD/PhD training in medicine.

Example projects (examples)

•  Processing Pixel‑seq runs from raw reads to spatial gene expression maps for brain and tumor tissues

•  Building and validating barcode → (x,y) maps and connecting sequencing reads back to spatial coordinates

•  Cell segmentation and spatial aggregation to produce single‑cell datasets for clustering and cell‑type annotation

•  ImmunoPixel‑seq analyses integrating spatial RNA with antibody‑derived tags / spatial protein readouts

•  Custom disease‑focused analysis workflows (e.g., neuroimmune interactions, tumor microenvironment niches, aging‑related changes)

What you’ll do

•  Process raw sequencing data (demultiplexing/QC → quantification) and generate run QC summaries and standardized outputs.

•  Map genes (and/or protein tags) to spatial barcodes: build/validate barcode maps, implement barcode error‑checking, and join counts to spatial coordinates.

•  Perform cell segmentation and spatial aggregation (image‑based and/or transcript‑informed) and establish practical QC checks.

•  Conduct downstream single‑cell and spatial analyses (clustering, annotation/label transfer, spatial neighborhoods/domains, spatial DE; figures and short analysis reports).

•  Automate and maintain pipelines using workflow tools (e.g., Snakemake/Nextflow) with clear documentation and reproducible environments.

•  DevOps‑lite / infrastructure support: maintain user‑space analysis environments (conda/uv, Docker/Apptainer), write SLURM job scripts, coordinate with IT on scheduled upgrades, and validate pipelines after upgrades (no enterprise sysadmin responsibilities).

Required qualifications

•  BS/BA in Computer Science, Applied Math, Bioinformatics, Computational Biology, EE, or a closely related field (or equivalent experience).

•  Strong programming skills in Python and basic shell scripting; comfort working with large files/datasets.

•  Familiarity with Linux and version control (Git); ability to write clear READMEs and well‑documented code.

•  Fundamentals in statistics/linear algebra; ability to reason carefully about QC, errors, and performance.

•  Interest in biology/medicine (e.g., coursework in biochemistry, genetics, or related areas) and willingness to learn domain context.

Preferred qualifications

•  Experience with single‑cell and/or spatial analysis tools (Scanpy/Squidpy, Seurat, scvi‑tools).

•  Experience with segmentation/image analysis (Cellpose, StarDist, QuPath, or similar).

•  Workflow automation (Snakemake/Nextflow) and containers (Docker/Apptainer); HPC/Slurm experience.

•  Practical experience working with NGS data formats and QC (FASTQ/BAM/CRAM, UMI/CB concepts).

•  Domain familiarity with brain, cancer, immunology, or aging datasets.

What we offer

•  Hands‑on experience with cutting‑edge spatial omics technologies (Pixel‑seq / ImmunoPixel‑seq).

•  Real ownership of production pipelines used for active research projects.

•  Mentorship and training in reproducible scientific computing, single‑cell/spatial analysis, and best practices for collaborative research.

•  Opportunities to contribute to manuscripts, figures, and method documentation (with co‑authorship where appropriate).

•  An inclusive, collaborative environment that values rigor, openness, and trainee development.

Appointment details

•  Location: Seattle, WA (University of Washington).

•  Start date: flexible (mutually agreed).

•  International applicants are welcome; work authorization/visa sponsorship and appointment terms follow UW policy.

Compensation & benefits

Salary range: $65,000–$70,000/year (commensurate with qualifications) plus UW benefits.

How to apply

Email Dr. Liangcai Gu at gulc (at) uw.edu with subject line: “RSE1 — Spatial Bioinformatics”

Please include:

1) CV or resume,

2) brief cover letter (≤1 page) describing your background, interests, and availability,

3) a link to a code sample (GitHub, class project repo, pipeline example, or a short example you can share), and

4) contact information for 2 references.

(If you don’t have public code, a short description of a technical project you built and your role is fine.)

Equal Opportunity

The University of Washington is an affirmative action and equal opportunity employer. We welcome applications from all qualified candidates.