Postdoc: Advanced Neuroimaging & ML for Brain Health

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

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