About the RoleYou will build and maintain a shared image-analysis core that turns image series into reliable measurements across our platforms, with tools scientists can use independently. Image registration is central to the role, both across image series and to anatomical references. Early work includes locating wells and identifying brain imaging planes to guide repeatable probe positioning, and extracting response measurements for screening and in-vivo imaging.
In this role, you will:- Develop image-based methods and scan strategies to locate wells and match brain imaging planes for repeatable probe positioning.
- Build analysis workflows for object and peak detection, background subtraction, drift correction, and response metrics such as rise and fall times.
- Develop and validate registration methods for reconstructed image series, quantifying motion and alignment accuracy.
- Develop registration methods to align ultrasound images with MRI and other anatomical references for imaging and targeting workflows.
- Agree metric definitions and acceptance criteria with scientists, including accuracy, repeatability, and failure conditions.
- Rigorously validate analysis methods with reference measurements, controls, and regression tests, assessing signal preservation and repeatability.
- Improve and maintain tested, documented Python tools that scientists can run independently.
- Integrate analysis methods with acquisition and reconstruction workflows and optimize runtime and memory use for large image datasets.
You might thrive in this role if you have:- Experience developing or substantially improving quantitative image-analysis workflows used by others.
- Strong practical image-processing and spatial-reasoning skills, including detection and image registration.
- Sound numerical and signal-processing judgment about how sampling, filtering, and correction affect measured responses.
- Strong scientific Python skills and experience maintaining tested, documented software.
- Practical judgment about runtime and memory use in image-analysis workflows.
- A disciplined approach to validation and honest reporting of uncertainty, limitations, and failures.
- Experience turning ambiguous scientific requests into useful workflows with the people who use them.
Useful, but not required:- Prior experience with multimodal image registration, particularly alignment to MRI.
- Ultrasound, microscopy, or other scientific imaging.
- Image-guided experimental automation.
- GPU or distributed image processing.
- Visualization tools used by scientists.
- Developing and evaluating learned image-analysis methods.
- Experience turning scientific Python prototypes into production-quality software, including work with build systems such as Bazel.
- Experience using AI tools or agents to develop scientific software and optimize processing pipelines.
If you're excited about this role but don't meet every qualification, please apply. As we build, we're hiring for complementary strengths to form a high-impact team.
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