Post Doctoral.Post Doctoral.Associate

University of Pittsburgh • Pittsburgh, PA

5h • Onsite

About The Position

We are seeking a highly skilled and motivated postdoctoral associate researcher to join an exciting multi-center project funded by the American Heart Association (AHA) Strategically Focused Research Network (SFRN). The successful Candidate will work on a high-impact initiative aimed at establishing a computational framework to model and predict the risk of aortic stenosis (AS). The successful Candidate will analyze and integrate high-throughput omics, large-scale imaging, and clinical data from large population databases and prospective clinical data from University of Pittsburgh Medical Center (UPMC) to map the full spectrum of early valve disease. Our research group operates at the intersection of data science and vascular medicine within the highly interdisciplinary environment of the Vascular Medicine Institute (VMI). We are dedicated to bridging the gap between "big data" and clinical application, combining computational innovation with experimental and clinical collaboration. By integrating multi-modal datasets, we strive to uncover the molecular and physiological drivers of cardiovascular disease, creating a unique space where novel computational hypotheses can be directly tested and validated by our experimental partners.

Requirements

• Ph.D. in image analysis, computational biology, bioinformatics, data science, or a related discipline
• Experience in statistical learning (demonstrable project in the relevant field)
• A strong publication record in the relevant field
• Strong motivation to successfully complete complex, collaborative projects.

Responsibilities

• Harmonization and analysis of image-derived phenotypes across different imaging modalities, including MRI, CT, and echocardiography.
• Development of machine/deep learning platforms to predict AS-related risk from multimodal features, including genetics, proteomics, and metabolomics.
• Identification of molecular factors to explain population risk heterogeneity
• Utilize computational tools for preventive drug prediction.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees