Positions relevant for ITK community members are available at the new Allen Institute of Neural Dynamics:
https://allenneuraldynamics.github.io/
Scientist - Machine Learning in Circuit Tracing
This Scientist will work with other quantitative and experimental scientists on high-priority problems in neuronal reconstruction and analysis that include (i) topology-preserving approaches to neuronal segmentation, (ii) deep learning-based analysis of morpho-molecular datasets, and (iii) high performance computing.
Data Infrastructure Engineer III
This skilled data engineer will design and operate a modern, cloud-first data platform that enables multiple scientific teams collecting peta-scale biological datasets to manage metadata, orchestrate automated computational workflows, and share data with the neuroscience community adhering to FAIR standards.
Software Engineer II - Image Registration
This machine vision software engineer will join a program to understand the long-range connectivity patterns of neurons whose activity underlies complex behavior and decision-making. In this role, the candidate will build robust, scalable image processing and analysis pipelines. A key component of these pipelines is multimodal image registration between individuals and standardized coordinate systems.
Software Engineer II - Computer vision
This software engineer to help understand the brain-wide connectivity of neurons whose activity underlies complex behaviors. They will employ existing and novel computer vision algorithms to label and extract objects, such as neurons and their connections, from tera- and petabyte-scale microscopy images.
Scientist - Applied Statistics and Machine Learning
This computational scientist will model peta-scale, multimodal neuroscientific data collected on cutting-edge data generation platforms. Potential projects include: 1) building detailed maps of brain structures based on single-cell transcriptomic profiles; 2) refining these maps based on high-throughput measurements of morphology and connectivity; 3) linking these maps with cell type-specific measurements of neural activity during behavior.