Post Doctoral Associate

University of Pittsburgh • Pittsburgh, PA

2d • Onsite

About The Position

The Department of Surgery, Division of Pediatric Surgery, at the University of Pittsburgh seeks a Postdoctoral Associate to work under the direction of Dr. Carolina Pinzon-Guzman. This is an exciting opportunity for a hard-working research scholar who is a highly self-motivated individual. The successful Candidate will provide advanced data analysis support for a basic and translational research program focused on congenital anomalies, including esophageal atresia/tracheoesophageal fistula and congenital diaphragmatic hernia. The position will be responsible for the analysis and interpretation of high-dimensional biological datasets, with an emphasis on bulk and single-cell RNA sequencing generated from patient-derived surgical tissues and organoid models. Key responsibilities include data quality control, statistical modeling, cell-type identification, differential expression analysis, pathway and network analysis, and integration of multi-omics datasets. The individual will work closely with the principal investigator to translate complex computational results into biologically meaningful insights regarding single-cell function and disease-specific molecular differences, supporting hypothesis generation, manuscript preparation, and grant applications.

Requirements

• PhD in Bioinformatics and Systems Biology or related field.
• Ability to independently conduct literature research.
• Ability to independently design and conduct experiments.
• Ability to independently carry out data analysis.
• Ability to independently report results.
• Effective communication skills.
• Evidence of effective writing skills.
• Evidence of effective interpersonal skills.

Responsibilities

• Provide advanced data analysis support for a basic and translational research program focused on congenital anomalies.
• Analyze and interpret high-dimensional biological datasets, with an emphasis on bulk and single-cell RNA sequencing.
• Perform data quality control, statistical modeling, cell-type identification, differential expression analysis, pathway and network analysis, and integration of multi-omics datasets.
• Translate complex computational results into biologically meaningful insights regarding single-cell function and disease-specific molecular differences.
• Support hypothesis generation, manuscript preparation, and grant applications.

Benefits

• Salary will be commensurate with relevant research experience.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree