Remote opportunity at
Convergent ResearchE11 Bio - Machine Learning Scientist I/II
E11 Bio, a focused research organization operating under Convergent Research, is seeking a Machine Learning Scientist I or II to join its interdisciplinary team. Located in…
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About This Role
E11 Bio, a focused research organization operating under Convergent Research, is seeking a Machine Learning Scientist I or II to join its interdisciplinary team. Located in Alameda, California, the non-profit organization is pursuing a neuroscience moonshot project aimed at advancing connectomics to the scale of whole mammalian brains by developing scalable brain-mapping technologies. In this role, the selected candidate will lead core machine learning pipelines focused on automated proofreading for…
Job Description
E11 Bio, a focused research organization operating under Convergent Research, is seeking a Machine Learning Scientist I or II to join its interdisciplinary team. Located in Alameda, California, the non-profit organization is pursuing a neuroscience moonshot project aimed at advancing connectomics to the scale of whole mammalian brains by developing scalable brain-mapping technologies. In this role, the selected candidate will lead core machine learning pipelines focused on automated proofreading for neuron and synaptic reconstructions derived from optical connectomics datasets. The position involves collaborating directly with microscopists, wet lab scientists, and various domain experts to enhance biological fidelity and scalability while working to lower segmentation and proofreading costs.
The ideal professional for this position is passionate about moonshot neuroscience, intrinsically motivated to work inclusively within an interdisciplinary team, and deeply committed to open science and transparency. Candidates should thrive in a tight-knit start-up environment where they can take long-term risks on ambitious scientific endeavors away from typical academic or for-profit pressures. The role provides an opportunity to maximize scientific impact and build relationships across the broader neuroscience community.
Responsibilities
- Build innovative machine learning methodologies for automated proofreading of segmentations across petabyte-scale optical connectomics volumes utilizing shape and barcode data.
- Manage the deployment of scalable workflows to ingest extensive connectomic datasets into standard proofreading platforms including WebKnossos and CAVE.
- Partner with industry and academic specialists to develop and expand tools designed for interactive visualization and automated proofreading.
- Design, execute, and assess scalable pipelines aimed at synapse detection and partner assignment within large optical connectomics datasets by combining morphological and protein labeling details.
- Construct machine learning-driven image processing utilities to eliminate major bottlenecks within data processing and analysis workflows.
- Uphold rigorous laboratory science standards, share findings via reports and presentations, and assist in drafting manuscripts, abstracts, and additional scientific materials.
Requirements
- Possess a Ph.D. in applied math, computer science, machine learning, computational biology, or a related science and engineering discipline, or have an equivalent history of publication.
- Demonstrate three to five years of relevant research or professional work experience highlighting independent execution of novel machine learning solutions.
- Showcase a robust foundation in computer vision alongside the application of machine learning tools toward large-scale microscopy dataset analysis.
- Exhibit familiarity with software engineering best practices such as code reviews and version control.
- Display strong communication, collaboration, and record-keeping abilities with a high level of attention to detail.
Qualifications
- Familiarity with graph, point, or sequence-based machine learning approaches including Transformers, GNNs, and Pointnets.
- Experience handling large chunked data formats like Zarr within cloud environments such as AWS or GCP.
- Prior exposure to large-scale connectomics tools and datasets including Neuroglancer, CATMAID, CAVE, and WebKnossos.
- A strong publication track record in peer-reviewed scientific journals.
Core Skills
Benefits
- Comprehensive PPO medical, dental, and vision insurance coverage along with parental leave.
- Generous time off policy accompanied by paid holidays.
- Matching 401(k) contributions up to 6 percent of the base salary.
- Daily lunches and plenty of healthy, energizing food options.
- Stipend dedicated to wellness and fitness activities.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the salary range for the Machine Learning Scientist position?
The base salary ranges from $130,000 to $225,000 per year, with a performance-based bonus up to 20 percent of the base salary and a 401(k) match up to 6 percent.
Where is this job located?
The position is located at E11 Bio in Alameda, California, operating as a focused research organization under Convergent Research.
What are the primary educational requirements for applicants?
Applicants must hold a Ph.D. in computer science, machine learning, applied math, computational biology, or a related science and engineering field, or possess a Ph.D.-equivalent publication history.
Is remote work permitted for this role?
The source posting does not specify whether remote work is permitted for this role.
Sample Interview Questions
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