AI-Enabled Spatial Neuropathology & Multi-Omics

Main responsibilities

• Generate high-quality single-cell and single-nucleus RNA-seq libraries (10x Genomics Chromium, multiome ATAC + GEX) from human postmortem brain and spinal cord, iPSC-derived neural cultures, and rodent CNS tissues.
• Execute spatial transcriptomics workflows (10x Atera, Xenium, or NanoString GeoMx DSP) and spatial proteomics workflows (CODEX/PhenoCycler, GeoMx protein, imaging mass cytometry) on FFPE and fresh-frozen CNS sections.
• Perform precision dissection, cryosectioning, and FFPE sectioning of human postmortem CNS tissue under appropriate biosafety conditions; manage tissue biobank inventory, sample QC, and chain-of-custody documentation.
• Conduct multiplex immunohistochemistry and immunofluorescence to characterize disease-relevant pathology (e.g., TDP-43 proteinopathy, tau, -synuclein, demyelination markers) and to validate findings from single-cell and spatial datasets.
• Operate and maintain confocal, widefield, and slide-scanning microscopy platforms; capture and curate imaging data to support quantitative neuropathology.
• Execute first-pass QC and exploratory analysis of single-cell and spatial datasets using standard pipelines (Cell Ranger, Space Ranger, Seurat, Scanpy, Squidpy); partner with computational team members for downstream analysis.
• Develop, optimize, and document standard operating procedures; train junior team members on established assays.
• Maintain rigorous electronic lab notebook records, contribute to internal data reviews, present results at group and cross-functional meetings, and contribute to publications, posters, and patent filings.
• Cook up with external academic collaborators, brain banks, and CRO partners on tissue acquisition, IRB documentation, and assay execution.

About You

• Education: BS with 4+ years OR MS with 2+ years, of relevant laboratory experience in neuroscience, molecular biology, cell biology, biomedical engineering, or a related discipline.
• Experience & Technical Skills:
  • Demonstrated hands-on proficiency with single-cell or single-nucleus RNA-seq library preparation (10x Genomics Chromium platform required).
  • Direct hands-on experience with at least one spatial transcriptomics or spatial proteomics platform (Visium, Xenium, MERFISH, GeoMx, CODEX/PhenoCycler, or equivalent).
  • Demonstrated experience handling and processing primary tissue, including cryosectioning and/or FFPE sectioning, with a track record of producing publication-quality histology.
  • Hands-on competence in immunohistochemistry, immunofluorescence, and fluorescence microscopy.
  • Hands-on experience applying AI/machine learning approaches to digital neuropathology, including the use of deep learning-based tools (e.g., QuPath with StarDist/Cellpose, HALO AI, Aiforia, or custom Python/PyTorch pipelines) for automated cell segmentation, tissue classification, and quantitative pathology readouts on whole-slide images.
• Soft Skills:
  • Strong organizational skills, meticulous record-keeping, and the ability to manage multiple parallel workflows in a deadline-driven environment.
  • Excellent written and verbal communication; comfort presenting data to scientific audiences.
• Preferred Qualifications:
  • Working knowledge of R or Python or AI tools (Cursor, Claude) sufficient to perform QC, generate exploratory plots, and interface with computational collaborators.
  • Direct experience with postmortem human CNS tissue and familiarity with brain bank operations and consent/IRB frameworks.
  • Experience with in vivo rodent procedures including blood micro-sampling, terminal collections, brain dissection and microdissection, CSF collection, and analyzing tissue samples from in vivo studies using molecular assays including NULISA, MSD, ELISA, and Western Blot.
  • Background in neurodegenerative disease research (ALS, FTD, Alzheimer's disease, Parkinson's disease, or multiple sclerosis).
  • Familiarity with iPSC-derived neuronal or glial models.
  • Prior pharmaceutical or biotechnology industry experience and exposure to GLP/GxP-adjacent documentation practices.
  • Co-authorship on peer-reviewed publications.