E11 Bio - Scientist, Tissue & Imaging Quality

Core Responsibilities

• Ensure consistent end-to-end quality across our in vivo sample preparation pipeline.
• Collaborate with technicians, including viral delivery and animal perfusion, tissue processing, and overall readiness for imaging and molecular readouts.
• Perform and troubleshoot stereotaxic injections and perfusions as needed to optimize our in vivo sample preparation pipeline and guide protocol improvements.
• Routinely evaluate injection and perfusion outcomes (viral labeling, tissue quality, use for downstream work) through microscopy and image analysis.
• Define, implement, and maintain sample quality rubrics (e.g. labeling density, barcode density) and ensure samples are scored consistently over time.
• Develop and maintain image-based workflows to generate quantitative QC metrics based on partnership and feedback with wet lab and computational staff.
• Design and perform experiments to improve sample quality when it is limiting for downstream applications.
• Extend quality assessment to RNA integrity and molecular preservation.

Required Qualifications

• Ph.D. in neuroscience, biology, bioengineering, or a related life-science or engineering field, or Ph.D.-equivalent working record
• 3–5 years of relevant research experience with a strong track record of end-to-end experimental ownership
• Demonstrated hands-on experience with in vivo sample preparation, including stereotaxic injections, perfusions, and tissue handling
• Experience acquiring and working with confocal and widefield microscopy data
• Experience developing or maintaining fit-for-purpose image-analysis workflows (e.g. Python scripts, Fiji macros, or equivalent) to support experimental iteration
• Strong organizational, documentation, and record-keeping practices and strong attention to reproducibility
• Excellent communication and collaboration skills, particularly across wet-lab, imaging, and computational teams

Preferred Qualifications

• Experience designing or applying quality control rubrics or scoring systems for biological samples or imaging data
• Familiarity with image-analysis pipelines for cell counting, morphology, spatial distributions, or intensity-based metrics
• Experience working in highly iterative or startup-like research environments and in work where roles span multiple technical domains