Postdoctoral Fellow: Computational Neuroimaging & ML

University of Pennsylvania Perelman School of Medicine; Erie (Erie County); On-site; USD 60,000 - 85,000; Full time

Job summary

University of Pennsylvania’s Perelman School of Medicine invites applications for two postdoctoral positions in the Center for Biomedical Image Computing and Analytics (CBICA), Radiology. The roles focus on computational neuroimaging, machine learning, and clinical neuroscience, funded by NIH.

Ideal candidates will have a PhD in a quantitative field and strong background in image processing, statistics, and deep learning with MRI/PET data. Visa sponsorship is welcome.

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.

Responsibilities

• Contribute to projects at the intersection of medical image analysis, machine learning, and clinical neuroscience.
• Develop computational methods for analyzing large-scale neuroimaging and clinical datasets.
• Work on two main directions: MRI/PET image analysis for aging and neurodegenerative diseases; ML on imaging and clinical data for disease characterization and prediction.

Skills

Image processing

Statistical analysis

Machine learning

Deep learning

Education

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

Job description

University of Pennsylvania’s Perelman School of Medicine invites applications for two postdoctoral positions in the Center for Biomedical Image Computing and Analytics (CBICA), Radiology. The roles focus on computational neuroimaging, machine learning, and clinical neuroscience, funded by NIH.

Ideal candidates will have a PhD in a quantitative field and strong background in image processing, statistics, and deep learning with MRI/PET data. Visa sponsorship is welcome.