Nextflow Jobs in Seattle, WA (NOW HIRING)

Job Summary:
The University of Washington is a leading institution dedicated to fostering an inclusive environment and advancing research. They are seeking a Research Scientist/Engineer 1 to contribute to computational biology projects, focusing on developing pipelines for spatial transcriptomics and related analyses.
Responsibilities:
• End‑to‑end data processing (BCL/FASTQ → QC → counts) – 20%
• Demultiplexing, adapter/quality trimming, UMI handling, alignment/quantification; generation of MultiQC reports and run manifests.
• Spatial barcode mapping & registration – 15%
• Build/validate barcode→(x,y) maps for Pixel‑seq; error correction; join gene/protein counts to spatial coordinates; QA of mapping rates.
• Segmentation & QC – 20%
• Apply/benchmark nuclei or whole‑cell segmentation (e.g., Cellpose/StarDist/SAM); maintain curated masks and QC thumbnails.
• Downstream single‑cell & spatial analysis – 20%
• Create annotated data objects (e.g., AnnData/Seurat); normalization, clustering, label transfer; spatial neighborhood/domain analysis; multi‑omic modeling for RNA+protein where applicable.
• Pipeline automation & reproducibility – 10%
• Implement/maintain Snakemake/Nextflow workflows with containers (Apptainer/Docker), CI tests, and clear documentation.
• Project support, collaboration & reporting – 7%
• Prepare figures/tables; concise analysis memos; contribute to methods sections.
• Light server/environment maintenance & upgrades (DevOps‑lite) — 5%
• Build and update containerized analysis environments, maintain conda/uv environments.
• DevOps‑lite & data stewardship – 3%
• Maintain analysis environments/containers; basic SLURM job scripts; coordinate with IT on storage/backup hygiene.
Qualifications:
Required:
• Bachelor's Degree in CS, Applied Math, Bioinformatics, Computational Biology, ECE and one year of relevant experience with Computational biology/bioinformatics.
• Programming & data: Python (numpy/pandas), basic R (Seurat/tidyverse), bash; Git; Linux.
• NGS data processing: BCL→FASTQ demultiplexing; adapter/quality trimming; UMI handling; QC with MultiQC; alignment/quantification to reference.
• Spatial omics: Pixel‑seq barcode→(x,y) mapping concepts; creation of spatially annotated objects (AnnData/Seurat).
• Segmentation: Practical use of Cellpose/FICTURE (or similar); basic image QC.
• Single‑cell & spatial analysis: Normalization, clustering, label transfer; spatial neighborhood/domain analyses (e.g., with Squidpy/Giotto).
• Reproducibility & automation: Snakemake or Nextflow; containerization (Apptainer/Docker); clean documentation; basic SLURM job submission.
• Communication: Clear writing of READMEs, short analysis memos, and figure captions for collaboration with biologists/clinicians.
• Linux/HPC usage; Slurm job submission, resource requests, and environment management.
Preferred:
• Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein integration.
• GPU experience: PyTorch/CUDA for segmentation/model inference.
• Data stewardship: DVC or equivalent data versioning; basic dashboarding/monitoring (Prometheus/Grafana).
• Domain breadth: Prior coursework/research in biochemistry or genetics; interest in medical/MD‑PhD pathways.
• DevOps‑lite: GitHub Actions CI, environment pinning, reproducible reference bundles, and runbooks.
• Experience assisting with server upgrades in collaboration with IT (CUDA/cuDNN & GPU driver stacks, Slurm client updates, module systems).
• Basic familiarity with configuration/monitoring for research workflows (e.g., Ansible basics, Prometheus/Grafana dashboards) under IT guidance.
• Storage and I/O awareness for high‑throughput data (scratch NVMe vs. bulk); performance troubleshooting for pipelines.
Company:
University of Washington is an educational institution that provides undergraduate, graduate, and research programs. Founded in 1861, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.