Postdoctoral Fellow in computational neuroimaging

University of Pennsylvania; Philadelphia (Philadelphia County); On-site; USD 60,000 - 75,000; Full time

Job summary

A prestigious academic institution in Philadelphia seeks a Postdoctoral Fellow in computational neuroimaging. The position emphasizes developing computational methods for analyzing neuroimaging and clinical datasets, focusing on brain health and disease. Ideal candidates should hold a PhD and possess strong skills in image processing and machine learning, including experience with MRI or PET data. The role is NIH grant funded and invites applicants requiring visa sponsorship.

Qualifications

• 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.

Responsibilities

• Develop advanced image analysis tools for MRI and PET data to study brain health.
• Apply machine learning methods to imaging and clinical data for disease characterization and prediction.

Skills

Image processing

Statistical analysis

Machine learning

Pattern recognition

Deep learning

Education

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

Job description

Postdoctoral Fellow in computational neuroimaging

Location: University of Pennsylvania - Perelman School of Medicine
Open Date: Mar 06, 2026
Deadline:

• 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.

Application Instructions

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

To apply, visit https://apply.interfolio.com/182811

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.