Research Scientist/Engineer
Listed on 2026-02-19
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IT/Tech
Data Scientist, Data Analyst
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.
Job DescriptionComputational 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.
Purpose Of The Research Project(s)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).
Duties And Responsibilities- End‑to‑end data processing (BCL/FASTQ → QC → counts) – 20%
- Demultiplexing, adapter/quality trimming, UMI handling, alignment/quantification; generation of Multi
QC 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.
Minimum RequirementsBachelor'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.
Additional Requirements- 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 Multi
QC; 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/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.
- Probabilistic modeling: scVI/scANVI/total
VI 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…
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