Postdoctoral Fellow in computational neuroimaging

University of Pennsylvania; Erie (Erie County); On-site; USD 60,000 - 78,000; Full time

Job summary

Two postdoctoral positions at the Center for Biomedical Image Computing and Analytics (CBICA) in Radiology, University of Pennsylvania, are available to advance computational neuroimaging and machine learning. The successful candidates will work on MRI/PET data analysis, biomarker extraction, and clinical outcomes prediction within NIH-funded projects.

Ideal candidates hold a PhD in a quantitative field and have strong expertise in image processing, ML, and deep learning with neuroimaging data.

Qualifications

• PhD in computer science, biomedical engineering, electrical engineering, applied mathematics, neuroscience, or a related quantitative field.
• Strong background in image processing, statistics, machine learning, or pattern recognition.
• Experience with deep learning and neuroimaging data (MRI/PET) is highly desirable.
• Applicants requiring visa sponsorship are welcome to apply.

Responsibilities

• Develop computational tools for MRI and PET data analysis.
• Apply machine learning to imaging and clinical datasets.
• Collaborate with researchers across radiology and CBICA.
• Prepare and publish results; contribute to NIH-funded projects.

Skills

Image processing

Statistical analysis

Machine learning

Pattern recognition

Deep learning

Education

PhD in quantitative field

Job 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.

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.

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

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.