A Postdoctoral Fellow position is available in the Neurodegeneration and Sleep Pathology Laboratory at Mayo Clinic under the leadership of Dr. Lea T. Grinberg. The laboratory investigates the biological basis of sleep and circadian dysfunction in aging and neurodegenerative diseases using deeply characterized human brain tissue. Our group has generated single cell, spatial transcriptomic, and spatial proteomic datasets spanning normal aging, Alzheimer disease, progressive supranuclear palsy, atypical Alzheimer disease variants, Lewy body disease, and related disorders, linked to detailed neuroanatomical, neuropathological, clinical, and sleep phenotyping. The fellow will join a collaborative, multidisciplinary team integrating molecular data with anatomy, cell biology, neural circuits, and disease mechanisms. We are seeking a candidate who will think first about the biological question and use genomic and computational tools to answer it. The ideal candidate will have a strong neuroscience foundation, preferably in neurodegeneration, and sufficient experience with large-scale omics data to independently formulate and test hypotheses. A candidate does not need to be a pipeline developer, software engineer, or dedicated bioinformatician. This position provides access to rare human brain datasets combining modern molecular profiling with detailed neuroanatomical, neuropathological, clinical, and sleep phenotyping. The fellow will develop and lead biologically driven projects within the laboratory’s broader mission of understanding sleep and circadian dysfunction across aging and neurodegenerative diseases. Potential questions include why sleep- and wake-regulating neurons show selective vulnerability or resilience; which molecular changes precede or follow neuronal loss; how different diseases alter common neural systems; and whether integration with public datasets can identify conserved mechanisms or therapeutic targets. The fellow will be encouraged to develop scientific ownership of projects, pursue directions emerging from the data, and contribute to high-impact publications, collaborative grants, and future funding opportunities.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree