Description
Post Doctoral.Post Doctoral.Associate
Med-Medicine - Pennsylvania-Pittsburgh - (26003096)
Postdoctoral Associate Researcher in Computational Biology/ Bioinformatics at the Vascular Medicine Institute (VMI), the University of Pittsburgh, School of Medicine, Department of Medicine
We are seeking a highly skilled and motivated postdoctoral associate researcher to join a computational systems biology project funded by NASA, focused on understanding how spaceflight-induced stress drives systemic failure across organs and identifying therapeutic strategies to mitigate these effects. The successful Candidate will work on a high-impact, data-driven initiative aimed at uncovering how microgravity, radiation, and related stressors induce coordinated molecular and cellular dysfunction across multiple organs. The project integrates bulk, single-cell, spatial, and time-series transcriptomic datasets from both animal models and astronaut biospecimens.
Our research group operates at the intersection of computational biology, systems medicine, and translational science within the Vascular Medicine Institute (VMI). We focus on integrating large-scale omics data with mechanistic modeling to uncover systemic drivers of disease. This project provides a unique opportunity to work on NASA spaceflight data while developing broadly applicable frameworks for understanding organ dysfunction and therapeutic intervention.
Key research responsibilities
• Integrate and analyze multi-modal transcriptomic datasets (bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, and time-series data).
• Identify disease molecular signatures under spaceflight and simulated conditions.
• Construct and analyze gene regulatory networks (GRNs) to infer upstream regulators.
• Develop and apply deep learningbased drug repurposing approaches to identify compounds that reverse space flight-induced regulatory disruptions.
Required skills and qualifications:
• Ph.D. in computational biology, bioinformatics, systems biology, data science, or a related field.
• Strong experience in transcriptomic data analysis, experience with spatial transcriptomics is a plus.
• Demonstrated expertise in statistical learning or machine learning.
• Experience with network biology, pathway analysis, or gene regulatory network inference is highly desirable.
• Ability to work independently on complex, interdisciplinary projects.
Interested applicants should apply via join.pitt.edu requisition #26003096
The University of Pittsburgh is an equal opportunity employer / disability / veteran.
Assignment Category: Full-time regular
Campus: Pittsburgh
Child Protection Clearances: Not Applicable
Required Attachments: Cover Letter, Curriculum Vitae
Optional Attachments: Research Statement
Assignment Category Full-time regular
PI284640856