Postdoctoral Fellow in computational neuroimaging

University of Pennsylvania Perelman School of Medicine; Pennsylvania; On-site; USD 52,000 - 70,000; Full time

Job summary

Two postdoctoral positions in computational neuroimaging and machine learning are available at the Center for Biomedical Image Computing and Analytics (CBICA), Radiology, University of Pennsylvania. The successful candidate will join a collaborative research environment focused on developing computational methods for large-scale neuroimaging and clinical datasets.

The roles involve advancing MRI/PET image analysis and applying machine learning to neurocognitive data, with NIH funding and visa

Qualifications

• PhD in a quantitative field (e.g., CS, BME, EE, math, neuroscience)
• Strong background in image processing, statistics, ML, pattern recognition
• Experience with deep learning and neuroimaging (MRI/PET) is highly desirable

Responsibilities

• Contribute to projects at the intersection of medical image analysis, ML, and clinical neuroscience
• Develop computational methods for large-scale neuroimaging and clinical datasets
• Explore two main research directions: advanced MRI/PET image analysis for aging and disease; ML on neurocognitive data for prognosis and diagnostics

Skills

Image processing

Statistical analysis

Machine learning

Deep learning

Pattern recognition

Python

TensorFlow/PyTorch

Education

PhD in computer science, biomedical engineering, electrical engineering, applied mathematics, neuroscience

Tools

Python

TensorFlow

PyTorch

scikit-learn

MRI data analysis

Job description

University of Pennsylvania: Postdoctoral Positions: Perelman School of Medicine Postdoctoral

Location

University of Pennsylvania - Perelman School of Medicine

Open Date

Mar 06, 2026

Description

• Faculty Mentor: Aristeidis Sotiras, PhD (Aristeidis (Aris) Sotiras, PhD - AIBIL)
• Department: Radiology
• Funding Source: NIH
• Number of positions: 2

Two postdoctoral positions in computational neuroimaging and machine learning are available at the Center for Biomedical Image Computing and Analytics (CBICA), Radiology, University of Pennsylvania. The successful candidate will join a highly collaborative research environment focused on developing computational methods for analyzing large-scale neuroimaging and clinical datasets to better understand brain health and disease. The postdoctoral fellow will contribute to projects at the intersection of medical image analysis, machine learning, and clinical neuroscience, with opportunities to work in two main research directions: (1) Development of advanced image analysis tools for MRI and PET data to study brain aging and neurodegenerative diseases, including Alzheimer’s disease. These projects involve large multi-cohort datasets and focus on extracting biologically meaningful imaging biomarkers. (2) Application of machine learning methods to imaging and clinical data from patients with neurocognitive disorders, with the goal of improving disease characterization, prediction of clinical outcomes, and personalized diagnostics. NIH grant funded. Applicants requiring visa sponsorship are welcome to apply.

Qualifications

The ideal candidate will have a strong background in image processing, statistical analysis, machine learning, or pattern recognition. Experience with deep learning and neuroimaging data (e.g., MRI or PET) is highly desirable.

Applicants should hold a PhD in computer science, biomedical engineering, electrical engineering, applied mathematics, neuroscience, or a related quantitative field.