E11 Bio - Associate Computational Scientist
About The Position
E11 Bio is a non-profit Convergent Research focused research organization in Alameda, California, working to advance connectomics toward whole-brain scale for humans and other mammals. The organization is pursuing neuroscience research through a scalable mammalian brain-mapping technology platform, with a collaborative, interdisciplinary team operating in a nimble, start-up-like environment. The Associate Computational Scientist will develop, maintain, and optimize workflows and infrastructure for processing large-scale brain-mapping data. The role supports reliable movement of petabytes of imaging data from microscope acquisition through completed, processed volumes. It combines data-pipeline work with hands-on maintenance of physical computing and network infrastructure, and daily collaboration with biologists and microscopists to identify ways scientific computing can accelerate research. The position will also develop practical laboratory tools for quality control, real-time data analysis, and AI-driven lab automation. This position is on-site in Alameda, California.
Requirements
- Bachelor's or master's degree in computer science, or another science or engineering field with a computational focus, or equivalent experience.
- Solid software development practices, including Python, Git, testing, and documentation.
- Fluency with AI-assisted, agentic development tools (such as Claude Code or Cursor) as part of a daily workflow, including directing coding agents and reviewing and testing their output.
- Data science fundamentals, including NumPy, SciPy, and working with large datasets.
- Comfort with Linux administration and computer hardware fundamentals, and willingness to work hands-on with physical equipment.
- Strong interpersonal and communication skills, including interest in translating between people with different areas of expertise.
- Curiosity about the brain and willingness to learn neuroscience on the job.
Nice To Haves
- Experience with servers, storage, networking fundamentals, or IT infrastructure.
- Experience with large-scale scientific data and machine-learning workflows, especially imaging data.
- Familiarity with HPC, job schedulers, distributed or cloud computing, and containers such as Docker or Apptainer.
- Experience in a wet-lab or applied-lab setting, ideally including software integration of laboratory hardware, such as writing custom control workflows.
- Experience with reproducible workflows and operations, including CI, GitOps, infrastructure as code, or FAIR data principles.
- Neurotechnology or BCI background.
Responsibilities
- Operate and improve automated pipelines that reliably process petabyte-scale volumetric microscopy data from acquisition to complete volumes.
- Maintain on-premises servers, storage, and networking; diagnose and replace failed hardware; coordinate with vendors; and support scaling across on-premises and cloud compute.
- Collaborate and coordinate with remote senior engineers to provide fast, reliable, hands-on support.
- Work with wet-lab scientists to identify, build, and own laboratory tools, including quality-control processes, live dashboards, and analysis tools.
- Train laboratory scientists on software tools and translate their experience into actionable feedback.
- Maintain and extend the pipeline-wide tracking dashboard to catch problems early, improve processes, and make data quality visible across the team.
- Contribute to agentic lab automation projects, including setting up AI-driven control of laboratory instruments with guidance from senior staff.
- Document work, prepare reports, and present results internally and externally.
- Learn existing data-processing workflows and operate and troubleshoot common problems.
- Own end-to-end processing of a new dataset, catching problems early and minimizing manual intervention.
- Assist remote engineers with building out on-premises hardware and network infrastructure.
- Gain familiarity with agentic lab-control processes and standards for connecting AI models to laboratory hardware.
- Build and own at least one new laboratory tool, such as a quality-control dashboard or analysis process.
- Interview key wet-lab scientists and microscopists to identify areas of friction.
- Maintain and contribute to the pipeline tracking dashboard and its metrics.
- Contribute multiple improvements to data-processing workflows that increase reliability, visibility, or throughput.
- Keep on-premises compute, storage, and network infrastructure well documented and highly available.
- Deliver laboratory automation projects alongside senior staff, such as agentic control of microscopes and other laboratory hardware.
- Extend the tracking dashboard with metrics and alerts that flag issues before they reach downstream processing.
Benefits
- Excellent medical, dental, and vision insurance through a PPO plan.
- Parental leave.
- Generous time off and paid holidays.
- 401(k) matching up to 6% of base salary.
- Daily lunches and ample healthy, energizing food.
- Stipend for fitness and wellness activities.
- Performance-based bonus of up to 20% of base salary.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
