Machine Learning Scientist I/II
Convergent Research · Posted Nov 13, 2026
- Remote, United States
- Remote
- Full-time · Mid
- 3–5 years
Develop scalable automatic proofreading methods leveraging barcode and shape information for optical connectomics datasets.
Responsibilities
- Contribute to developing innovative ML approaches for automatic proofreading of segmentations in large PB-scale optical connectomics volumes, leveraging shape and barcode information
- Own the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE)
- Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization
- Develop, implement, and evaluate scalable pipelines for synapse detection and partner assignment in large-scale optical connectomics datasets, integrating morphological and protein labeling information
- Identify and build ML-based image processing tools that remove key bottlenecks in our data processing and analysis pipeline
Requirements
- 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
- Nice to have: Graph ML methods (GNNs, Transformers, Pointnets)
- Nice to have: Sequence ML methods
- Nice to have: Point based ML methods
- Nice to have: Processing large chunked data (Zarr)