As a postdoc, you will play a key role in the success of a collaboration between Centaur Labs and Brigham and Women's Hospital (BWH) to develop large-scale labeled datasets of ultrasound clips, as well as state-of-the-art deep learning algorithms trained on those datasets.
You will be employed by Centaur Labs, but you will also have an appointment with and work closely with researchers at BWH.
Your objectives will include:
- Serving as a project manager overseeing work at BWH to de-identify and clip ultrasound videos, and then secure transfer of clips to Centaur Labs for labeling.
- Drafting and submitting any necessary amendments to IRB protocols.
- Working with the Centaur Labs team to ensure that the labeling pipelines and procedures will produce high-quality, clinically relevant labels for AI development.
- Conducting IRR analyses on labelers from the Centaur Labs network to identify optimal methods for statistically weighting and combining multiple rater opinions.
- Development and validation of state-of-the-art deep learning algorithms.
- Manuscript writing and preparation, including work on releasing deep learning algorithms in standardized formats to make them widely accessible to the broader machine learning and healthcare communities.
- This is a postdoc position, and applicants must have a PhD in data science, computer science, or a degree that involved large-scale medical image analysis (e.g., neuroscience, computational biology).
- Required skills include SQL, Amazon Web Services (AWS), and deep learning experience with medical image and/or video datasets.
- Experience building computer vision models.
At Centaur Labs, we label data (X-rays, DICOMs, text etc.) to enable breakthroughs in medical AI.
Our novel approach uses collective intelligence to aggregate opinions from experts and students all over the world, who provide these opinions on our gamified app, DiagnosUs. Our customers include leading AI startups and prominent research organizations.