Postdoctoral Research Scholar - AI Imaging and Retinal Disease

The Department of Ophthalmology and Visual Sciences is seeking a Postdoctoral Scholar (FP01) - AI Imaging & Retinal Disease who is interested in ophthalmology to assist in refinement of AI models as well as validation of new biomarkers and data analysis to be able to predict whether patients will be responsive to anti-VEGF injections and corticosteroids. This position will be supervised by Elliott H. Sohn, MD, FASRS, FARVO. Duties of the Postdoctoral Scholar will include:

DME and AI-driven biomarkers

Initial focus will be placed on projects designed to refine and validate artificial intelligence (AI) algorithms for analyzing OCT imaging in diabetic macular edema (DME).

• Data processing and image annotation to support development of AI models trained on OCT scans from DME patients, including DRCR datasets.
• QA of segmentation of retinal layers and fluid compartments using and validating automated tools such as Deep LOGISMOS.
• Analysis of clinical biomarkers, including linking OCT-derived features with visual acuity outcomes in patients treated with anti-VEGF agents or corticosteroids.
• Subject re-ascertainment and coordination of blood sample collection for a cohort of patients
• Bioinformatics and immune system profiling, using PBMCs from relevant subjects to investigate the immunologic basis for differential treatment response.
• Active involvement in statistical analysis and manuscript preparation.
• Contribution to abstract submission and presentation of results at national meetings (e.g., ARVO).

This work parallels and builds on efforts already underway in neovascular AMD and has significant public health implications for improving DME treatment response predictions and therapeutic decision-making.

AMD Imaging and Immunogenetics

A broader focus of the Research Assistant role will be contributing to ongoing AMD studies that integrate genetic, immunologic, and AI-based OCT biomarkers:

• Subject re-ascertainment and coordination of blood sample collection for a cohort of patients genotyped for MMP9, CFH, and ARMS2 variants.
• Support immunophenotyping and multiplex cytokine profiling of AMD patient PBMCs.
• Assist in analysis of genotype-phenotype correlations by combining OCT imaging biomarkers with clinical and immune profiles to correlate and predict treatment outcomes in neovascular AMD.
• Manual OCT segmentation for AI model validation and QA
• Integration of data across AMD and DR projects to support shared analytic frameworks, reflecting a systems-level approach to retinal disease mechanisms.

EZ band segmentation

* Assist in development and application of automated EZ band segmentation to longitudinal datasets of patients with MacTel and AMD

Research (Interdisciplinary training and scholarly output)

• Regular participation in lab meetings, journal clubs, and departmental and university-wide seminars across engineering, medicine, and vision research.
• Close collaboration with engineers, biostatisticians, and immunologists.
• Gain mentorship experience through peer interactions and regular guidance from Dr. Sohn, lab members and collaborating faculty.

Education Requirement: Requires the practical or academic knowledge of clinical ophthalmology, AI, image analysis, and statistics plus the ability to translate, adapt and apply this knowledge that is generally associated with a PhD or MD, or an equivalent combination of education and progressively responsible work experience.

Required Qualifications:

• Excellent written, verbal and interpersonal communication skills
• Strong organizational skills
• Experience working independently and in a group setting
• Ability to coordinate multiple projects; proficiency with computer software including Microsoft Word and Adobe Acrobat
• Familiarity with databases and data entry
• Proficiency with R

Desirable Qualifications:

• Knowledge of medical terminology
• Experience in a healthcare or ophthalmology or setting
• Knowledge or previous coursework in the research process
• Demonstrated ability to multi-task and excellent time management skills
• Proficiency with Python