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California, United States
Onsite
E11 Bio is on a mission to advance connectomics towards whole brain scale for humans and other mammals. We are a collaborative and interdisciplinary team of scientists and engineers engaged in a neuroscience moonshot project to develop a radical technology platform for scalable mammalian brain mapping. E11 Bio is a non-profit Convergent Research focused research organization located in Alameda, California, pursuing blue-skies neuroscience research yet operating like a nimble, tight-knit start-up. Read our technology roadmap.
E11 Bio is seeking a mission-aligned experimental scientist, equally at home at the bench, the microscope, and in quantitative data analysis, who brings an engineering approach to the full pipeline, from sample preparation through molecular readout tools and microscopy. This role involves both optimizing the physical preparation of the tissue and implementing agentic microscopy. Reporting to the Barcoding Lead, you will define what high-quality tissue means quantitatively and will drive the improvement of high quality morphology and protein readout by working closely with molecular biology, imaging, and computational teams to support whole-brain connectomics.
Develop and deploy an assay to systematically evaluate and improve the fixation quality and preservation of brain tissue
Establish and integrate quantitative metrics of molecular readout e.g. protein retention, antigenicity, and labeling quality across tissue preparation conditions
Drive the development of data-analysis pipelines to routinely generate key performance indicators of sample tissue quality
Work closely with in vivo research technicians to design experiments, evaluate results, and optimize SOPs
In collaboration with external and internal partners, drive agentic control and quality control of automated microscopy to enable consistent data quality over long acquisitions
In collaboration with external and internal partners, extend agentic control beyond acquisition to the everyday steps of the sample pipeline (e.g. liquid handling, staining, gelation, and intermediate readouts)
In collaboration with external partners, source new binders, including via novel design approaches, against synaptic and barcode targets
Characterized how much perfusion quality varies between brains, measured in fixed tissue, and the effect of this variability on downstream morphology outcomes
Deployed an assay or metrics that reliably allows samples to be ranked before entering a production run
Established a rubric for tissue artifacts at the M3 level, covering how the tissue and how this affects overall reconstruction ability
Recorded a measurable > 20% improvement in expanded ultrastructural image quality compared to current baseline perfusion & gelation protocol
Deployed real-time agentic control on at least one microscope and demonstrated production acquisitions with agent monitoring instead of human
External AI-driven epitope–binder collaboration launched with agreed scope
80% of samples entering gelation at E11 meet or exceed our sample quality threshold (rolling average)
If tissue artifacts affect segmentation, 80% of samples entering gelation at E11 meet or exceed our tissue quality threshold (rolling average)
Incorporated protein retention, antigenicity, and specificity as per-stage metrics across the sample generation pipeline and demonstrated their predictive power for key downstream outcomes (e.g. segmentability)
Agentic control and fault detection running across parallelized microscopes with measured increase in unattended acquisition time without loss of quality
Identified and validated multiple cocktails of binders for stratifying excitatory and inhibitory synapses
