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About the role

Focusing on cross-disciplinary research in scientific machine learning, the full-time salaried Postdoctoral Researcher in Machine Learning will develop innovative methods for predictive modeling across various experimental scales and conditions, addressing data sparsity and modality differences.
Key responsibilities: Develop methods to combine evidence from different experimental scales for accurate predictions Innovate learning techniques, including multi-modal and surrogate modeling approaches Collaborate with multidisciplinary teams to integrate diverse data sources and conditions in modeling effortsRequired qualificationsRecent PhD graduate within the last three years Demonstrated experience in developing machine learning models for scientific or engineering systems Experience in learning from one set of conditions and predicting in another with differing distributions Proficiency in combining data with varying modalities and experimental conditions Experience in physics-informed and hybrid modeling techniques

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JOB OVERVIEW

Experience level

Senior

Location

New York, NY

Occupation

Data Scientists

Industry

Research and Development in the Physical, Engineering, and Life Sciences

Posted

3 days ago

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