Research Scientist/Engineer 1

About the role

The position involves developing and operating robust, reproducible pipelines for transforming raw sequencing data into high-quality, spatially resolved single-cell datasets. It also entails delivering disease-focused analyses that advance mechanistic discovery and translational hypotheses.

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)
• Implement CI tests and clear documentation
• Project support, collaboration & reporting – 7%
• Prepare figures/tables
• 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

Requirements

• Bachelor's Degree in CS, Applied Math, Bioinformatics, Computational Biology, ECE with 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.

Desired Requirements

• 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.

Compensation, Benefits & Position Details

Pay Range Minimum: $65,004.00 annual
Pay Range Maximum: $70,008.00 annual
Benefits Other Compensation: For information about benefits for this position, visit here

Shift: First Shift (United States of America)
Temporary or Regular: Regular
FTE (Full-Time Equivalent): 100.00%