About the position
Job Description
- Developing new statistical methods to model multimodal
neuroimaging data, multi-omics data, electronic health record (EHR)
and genetics data which are measured by longitudinally and
cross-sectionally.
- Developing and applying machine learning and AI approaches to
identify interactive topological relationships between various
imaging modalities and multi-omics during aging and
development.
- Implementing computationally intensive algorithms on
high-performance computational clusters .
- Developing AI/ML-based causal inference models for real-world
evidence applications (e.g., target trial emulations- TTE)
- Developing data integration methods to combine multiple massive
datasets (UKBB, HCP, ENIGMA, and etc) and local trials and
observational studies (e.g, UMMS EHR).
- Manuscript drafting and preparation.
- Performing other duties as assigned
Responsibilities
Post Doctoral Fellow.
Qualifications
Doctorate or recognized terminal degree in the field of
specialization. Demonstrated research abilities. May require
unrestricted license in the State of Maryland.
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