Postdoctoral Fellow in computational neuroimaging

About the role

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.

Responsibilities

• Contribute to projects at the intersection of medical image analysis, machine learning, and clinical neuroscience
• Develop advanced image analysis tools for MRI and PET data to study brain aging and neurodegenerative diseases, including Alzheimer’s disease
• Extract biologically meaningful imaging biomarkers from large multi-cohort datasets
• Apply machine learning methods to imaging and clinical data from patients with neurocognitive disorders
• Improve disease characterization, prediction of clinical outcomes, and personalized diagnostics

Requirements

• 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
• PhD in computer science, biomedical engineering, electrical engineering, applied mathematics, neuroscience, or a related quantitative field

Qualifications

• Required documents for upload: CV, Research statement, at least 3 references

Skills

• Image processing
• Statistical analysis
• Machine learning
• Pattern recognition
• Deep learning
• Neuroimaging data (MRI, PET)

Benefits

• NIH grant funded

Pay

• TBD

Schedule

• TBD

Benefits

• TBD

Application Instructions

• Applicants requiring visa sponsorship are welcome to apply

Equal Employment Opportunity Statement The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.