Post-Doctoral Fellow B - SOM MPRC Administration

University of Maryland, Baltimore (UMB); Baltimore (MD); On-site; USD 60,000 - 90,000; Full time

Job summary

The University of Maryland, Baltimore (UMB) is seeking a Postdoctoral Fellow to advance statistical methods for multimodal neuroimaging, multi-omics, EHR, and genetics data. The role involves applying machine learning and AI to uncover interactive relationships across aging and development, and implementing intensive algorithms on high-performance clusters.

Responsibilities include developing AI/ML-driven causal inference models for real-world evidence, integrating large datasets such as UKBB,

Qualifications

• Doctorate or terminal degree in the field of specialization.
• May require unrestricted license in the State of Maryland.

Responsibilities

• Develop statistical methods to model multimodal neuroimaging, multi-omics, EHR and genetics data.
• Apply machine learning and AI to identify interactive relationships between imaging modalities and omics during aging and development.
• Run computationally intensive algorithms on high-performance clusters.
• Develop AI/ML-based causal inference models for real-world evidence applications (e.g., target trial emulations).
• Develop data integration methods to combine large datasets (UKBB, HCP, ENIGMA, UMMS EHR).
• Draft and prepare manuscripts.
• Perform other duties as assigned.

Skills

Statistical methods

Machine learning

AI approaches

Data integration

Neuroimaging

Genomics & EHR

Education

Doctorate or terminal degree

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

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.