NYU Grossman School of Medicine is seeking to advance its stroke foundation modeling study by developing innovative and impactful models for prognosis of stroke using AI and machine learning techniques.
Requirements
- Masters in Data Science, Machine Learning, Computer Science or related area
- One year data analysis/machine learning experience or equivalent combination of education and experience
- Familiarity with major machine learning models and data mining techniques
- Able to write code well in Python, R, or C++
- Familiarity with electronic health record databases
- Familiarity with data driven modeling (including gathering and cleaning data, exploratory analysis, implementing models, error analysis, and presenting the findings)
- Deep interest in Health AI
Responsibilities
- Design and building multimodal (including 3D imaging, and EHR based) foundation models
- Preprocessing of large volumes (100s of TB) of dicom images, EHR data, clinical notes
- Training and monitoring training of large AI models
- Benchmarking results against other state of the art open-source models
- Reporting and communicating findings to the clinical and technical teams
- Working with large, complex and noisy clinical datasets for solving challenging problems in the healthcare domain
- Prepare and present results, reports, both oral and written, to a variety of audiences, concerning processes, models, evaluation, and impact (ROI)
Other
- Qualified candidates must be able to effectively communicate with all levels of the organization
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- Masters in Data Science, Machine Learning, Computer Science or related area
- One year data analysis/machine learning experience or equivalent combination of education and experience
- Demonstrated skills in design and implementation of complex AI models
- Ability to work with all levels of the organization
