Postdoctoral Researcher: Biomedical Informatics & ML

University of Pittsburgh; Pittsburgh (Allegheny County); On-site; USD 60,000 - 80,000; Full time

Job summary

The University of Pittsburgh is seeking a highly motivated Post Doctoral Associate to contribute to federally funded projects in machine learning, regulatory genomics, single-cell multi-omics, spatial transcriptomics, and precision oncology.

You will apply and develop computational methods, take ownership of research projects, and advance them toward reproducible software, scientific deliverables, and peer-reviewed publications.

Qualifications

• PhD in computational biology, bioinformatics, biostatistics, statistics, mathematics, computer science, or a related quantitative field.
• Strong programming skills in Python and/or R.
• Demonstrated expertise in machine learning, statistics, omics data analysis, or computational biology.
• Ability to translate broad research objectives into specific analyses, timelines, and deliverables with limited supervision.
• Evidence of completing projects through peer-reviewed publications, software releases, or other substantive research outputs.

Responsibilities

• Lead computational projects from study design and data processing through modeling, validation, biological interpretation, and publication.
• Analyze large-scale bulk, single-cell, multi-omic, and spatial datasets.
• Develop and evaluate machine-learning methods for classification, prediction, multimodal integration, and regulatory inference.
• Apply rigorous validation practices, including data partitioning, cross-validation, baseline comparisons, external validation, and assessment of bias and generalizability.
• Develop reproducible, well-documented, version-controlled, and open-source software.
• Prepare publication-quality figures, manuscripts, presentations, and grant reports.
• Collaborate effectively with computational, experimental, and clinical investigators.
• Provide regular, structured progress updates and communicate challenges and delays promptly.
• Meet milestones and deadlines, respond to feedback, and complete revisions and action items.
• Support mentorship of junior researchers, as appropriate.

Skills

Python

R

Machine learning

Statistics

Computational biology

Education

PhD in computational biology or related field

Tools

PyTorch

TensorFlow

High-Performance Computing

Job description

The University of Pittsburgh is seeking a highly motivated Post Doctoral Associate to contribute to federally funded projects in machine learning, regulatory genomics, single-cell multi-omics, spatial transcriptomics, and precision oncology.

You will apply and develop computational methods, take ownership of research projects, and advance them toward reproducible software, scientific deliverables, and peer-reviewed publications.