Research Scientist​/Engineer

Field of Research

Computational biology/bioinformatics with emphasis on spatial transcriptomics, proteomics, and immunosequencing using Pixel‑seq and an immune receptor‑focused multimodal expansion ("Immuno Pixel‑seq"). Work includes NGS data processing, spatial barcode mapping, single‑cell & spatial analysis, and cell segmentation in brain, tumor, and other tissues.

Build and operate robust reproducible pipelines that transform raw sequencing + barcode map into high‑quality, spatially resolved single‑cell datasets and deliver disease‑focused analyses that advance mechanistic discovery and translational hypotheses (e.g., tumor microenvironment, neuroanatomical circuits).

To build and operate robust, reproducible pipelines that transform raw sequencing + barcode map into high‑quality, spatially resolved single‑cell datasets; to deliver disease‑focused analyses that advance mechanistic discovery and translational hypotheses (e.g., tumor microenvironment, neuroanatomical circuits).

• 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/Star Dist/SAM); maintain curated masks and QC thumbnails.
• Downstream single‑cell & spatial analysis – 20%:
  Create annotated data objects (e.g., Ann Data/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 (Dev Ops‑lite) – 5%:
  Build and update containerized analysis environments, maintain conda/uv environments.
• Dev Ops‑lite & data stewardship – 3%:
  Maintain analysis environments/containers; basic SLURM job scripts; coordinate with IT on storage/backup hygiene.

This position is eligible for H‑1B sponsorship.

Bachelor's Degree in CS, Applied Math, Bioinformatics, Computational Biology, ECE and one year of relevant experience with Computational biology/bioinformatics.

Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements, such as a license, certification, and/or registration.

• 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 (Ann Data/Seurat).
• Segmentation:
  Practical use of Cellpose/Figure (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.

• 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.
• Dev Ops‑lite:
  Git…