Postdoctoral Fellow-MSH-20093-054

We are seeking an innovative and highly motivated Research Scientist to join our interdisciplinary team working on cutting-edge projects to understand the pathogenesis and genetic underpinnings of Frontotemporal Dementia (FTD). The successful candidate will lead efforts leveraging artificial intelligence (AI) techniques, including machine learning and computer vision, to analyze whole slide images and correlate these findings with genetic and transcriptomic data. The goal of this research is to develop novel, robust biomarkers for Progressive Supranuclear Palsy (PSP) and other subtypes of FTD.

Develop and apply machine learning and computer vision algorithms to analyze neuropathological whole slide images of brain tissue.

Integrate imaging data with genetic, proteomic, and clinical datasets to identify novel biomarkers associated with FTD and related neurodegenerative disorders.

Collaborate closely with clinicians, neuropathologists, geneticists, and bioinformatics teams to facilitate data integration and interpretation.

Prepare research manuscripts, progress reports, and contribute actively to grant applications.

Present findings at local, national, and international scientific meetings.

PhD or equivalent degree in Neuroscience, Computational Biology, Bioinformatics, Computer Science, or a related field.

Demonstrated experience applying AI methods, particularly deep learning and computer vision, to biological or medical imaging data.

Proficiency in programming (e.g., Python, R), experience with data analysis and visualization tools.

Familiarity with neurodegenerative diseases, genetics/genomics, and neuropathology preferred but not required.

Strong communication, collaboration, and organizational skills.

Prior research in computational biology