Scientific Lead, Molecular Characterization
Listed on 2026-07-01
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Research/Development
Research Scientist, Biotech Research
Position Summary
The Scientific Lead position would be the principal architect for spatial biology and long-read genomics within the Molecular Characterization team in Discovery Technologies, responsible for developing, optimizing, and scaling these platforms in support of Oncology drug discovery Molecular Characterization team sits at the intersection of genomics, proteomics, and emerging molecular technologies, providing cutting‑edge platform capabilities across Lilly's discovery portfolio. The central mandate is invention: defining what next‑generation spatial and long‑read platforms can do, and building the infrastructure to realize their full potential within the group.
The successful candidate will possess deep, applied expertise in spatial transcriptomics (e.g., Visium HD, Cos Mx, Xenium), with working knowledge of long‑read sequencing (Pac Bio/Nanopore) and demonstrated experience in the automation of complex NGS workflows. Of equal importance is an entrepreneurial scientific mindset, a genuine drive to evaluate and deploy emerging tools that have not yet been established as standard practice within the field.
This is a hands‑on role where direct experimentation and platform development are central to scientific impact, with growing opportunities to shape scientific direction and mentor junior team members as the platforms mature. This position requires close collaboration with Oncology project teams, automation specialists, histology, and discovery informatics to translate novel molecular insights into actionable biology.
- Design and lead the development of spatial transcriptomics and multi‑modal spatial workflows, encompassing tissue optimization, library construction, and end‑to‑end data generation using platforms such as Visium HD, Cos Mx, and Xenium.
- Drive the integration of spatial transcriptomics with complementary modalities, including spatial proteomics (e.g., Cos Mx protein panels, CODEX/Pheno Cycler) and single‑cell data, to generate comprehensive tissue‑level molecular maps.
- Establish and continuously improve tissue processing standards for diverse sample types relevant to Oncology (FFPE, fresh‑frozen, bone marrow, cryosections), with a focus on maximizing data quality from challenging or low‑input specimens.
- Develop image analysis pipelines in collaboration with discovery informatics, including tissue segmentation, cell type deconvolution, and morphological co‑registration using tools such as QuPath, HALO, or equivalent platforms.
- Evaluate emerging spatial technologies on an ongoing basis and translate promising platforms into internal capabilities through systematic feasibility assessment and implementation planning.
- Scale long‑read sequencing workflows (Pac Bio and Oxford Nanopore) for applications including structural variant detection, isoform characterization, epigenetic sequencing (e.g., methylation, Fiber‑seq), and custom targeted approaches.
- Contribute to automation of NGS and spatial library preparation protocols in collaboration with automation and histology specialists.
- Develop custom targeted panels and probe/index designs for the spatial platforms to address specific genomic and transcriptomic questions posed by Oncology project teams.
- Establish protocol QC frameworks and performance benchmarks to ensure data integrity across all high‑throughput molecular platforms.
- Apply and adapt spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) to process, visualize, and interpret spatial transcriptomics datasets in close partnership with the discovery informatics team.
- Work with bioinformaticians to design and evaluate computational workflows for long‑read data, including isoform quantification, structural variant calling, and base modification detection.
- Serve as the internal scientific authority on spatial and long‑read sequencing platforms; advise Oncology project teams on platform selection, experimental design, and interpretation.
- Provide mentorship and hands‑on coaching to junior scientists; build a team culture grounded in technical rigor, creative problem‑solving, and collaborative execution.
- Establish and manage relationships with academic…
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