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E11 Bio - Machine Learning Scientist at Convergent Research – Alameda, California

Convergent Research
Alameda, California, 94501, United States
Posted on
Updated on
Salary:$130750 - $174760Job Function:Science

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About This Position

E11 Bio - Machine Learning Scientist

E11 Bio is a Focused Research Organization (FRO) with a long-term mission to make connectomics scalable and cost-effective for mammalian brains first for mice and eventually for humans.

We have recently developed PRISM, a platform technology for low cost optical connectomics. PRISM integrates advances in genetic cell barcoding, multiplexed expansion microscopy, and Machine Learning (ML)-based spatial reconstruction to solve key bottlenecks in data acquisition and analysis. We anticipate PRISM will reduce the cost of connectomics 100-fold and thereby transform neuroscience, treatments for brain disorders, and neuro-inspired computing.

E11 Bio is seeking a creative and mission-driven Machine Learning Scientist to develop and deploy novel methods to transform large-scale light microscopy data into discoverable synaptic connectivity information. In this role, you will own core ML pipelines for synapse detection and assignment in optical connectomics datasets, working closely with wet lab scientists, microscopists, and domain experts to ensure biological fidelity and scalability. Your work will directly support E11s goal of making reliable connectomic data accessible to the broader neuroscience community.
Responsibilities
  • Develop, implement, and evaluate scalable pipelines for synapse detection and partner assignment in large-scale optical connectomics datasets, integrating morphological and protein labeling information
  • Collaborate with wet lab scientists and domain experts to develop methods for detecting and classifying cellular and synaptic subtypes
  • Take ownership of structuring and organizing connectivity data into well-defined data models, and building developer-facing tooling to maximize the long-term usability, accessibility, and impact of generated connectivity data
  • Assist in any ML-adjacent image processing needs that may arise during scaling of the processing and analysis pipeline (e.g. image volume registration, multimodal feature extraction, label-free prediction etc.)
  • Collaborate closely with users and stakeholders to deliver clear, accurate, and actionable connectivity information
  • Partner with wet lab, microscopy, and computational teams to optimize data analysis workflows and inform data acquisition strategies
Required qualifications
  • Ph.D. in computer science, machine learning, applied math, computational biology or a related field in science and/or engineering or Ph.D.-equivalent publication history
  • 3-5 years of relevant work or research experience, with strong history of independent and autonomous execution of novel ML solutions
  • Strong background in computer vision and applying ML tools to the analysis of large microscopy data sets
  • Experience with software engineering best practices (e.g. version control, code reviews, etc)
  • Excellent communication and collaboration skills, record keeping ability, and attention to detail
Preferred qualifications
  • Experience with large scale connectomics datasets, tools, and database infrastructure (e.g. Neuroglancer, CATMAID, CAVE)
  • Familiarity with distributed processing frameworks for large-scale volumetric data (e.g. Dask, Daisy, Volara)
  • Experience with Python-based ML libraries such as PyTorch, TensorFlow, and Gunpowder
  • Experience developing database APIs and data services (e.g. PostgreSQL, Neo4j, BigTable), as well as user-facing data visualization tools (e.g. Dash, Plotly, D3)
In the first six months, you will have
  • Developed and deployed a robust pipeline for the routine detection of excitatory and inhibitory synaptic contacts between reconstructed neurons
  • Supported the team in diverse image processing challenges encountered in the process of scaling our pipeline
Within two years, you will have played a critical role in
  • Delivering accurate, discoverable, and actionable connectivity data to users through close collaboration with internal and external stakeholders
  • Expanding the impact and capabilities of the PRISM platform by integrating information on cell types, synaptic properties, and other cellular and subcellular features
You would love this job if
  • You are passionate about moonshot neuroscience, and want to broadly accelerate science through long-term commitment to a high-impact project with a tight-knit team
  • You have a strong desire and intrinsic motivation to work collaboratively and inclusively as part of an interdisciplinary team science effort
  • You are committed to the ethos of open science, and want to see your work transparently disseminated
  • Youre mission-driven, and are seeking an environment where you can take long-term risks on moonshot science, shielded from academic or for-profit incentives
  • Youre seeking a high-leverage, non-traditional opportunity to maximize the impact of your science, establishing relationships with key stakeholders in the neuroscience community
Base Salary Range: $130,750 - 174,762
Bonus: Performance-based, up to 20% of base salary
401k match: up to 6% of base salary
Total potential compensation range: $164,745 - $220,200
E11 Bio, LLC is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. We do not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. We strive for a healthy and safe workplace and strictly prohibit harassment of any kind.

$130,750 - $174,760 a year

Job Location

Alameda, California, 94501, United States

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