Postdoctoral Researcher in Neuroimaging and Integrative Brain Analyses

Location: University of Pennsylvania - Perelman School of Medicine

Open Date: Nov 04, 2026

The Platt Laboratory in the Department of Neuroscience at the University of Pennsylvania Perelman School of Medicine seeks a Postdoctoral Researcher to lead neuroimaging and integrative molecular analyses of brain aging in a naturalistic nonhuman primate model. The position is supported by a newly awarded National Institute on Aging U19 grant (U19AG092410) investigating the causes, consequences, and modifiers of aging heterogeneity in the Cayo Santiago rhesus macaque population, one of the world’s most extensively characterized free-ranging primate populations.

The successful candidate will develop and apply neuroimaging pipelines to characterize region-specific patterns of brain aging using ex vivo structural MRI data acquired from archived macaque brain hemispheres on Penn’s 7T scanner across the full adult lifespan. In parallel, the candidate will lead integrative analyses of brain-derived molecular datasets, including bulk RNA sequencing, DNA methylation, and potentially single-cell or spatial transcriptomics, to connect structural and molecular aging signatures across the same individuals.

The Postdoctoral Researcher will integrate neuroimaging and molecular brain measures with physiological, behavioral, social, and cognitive aging domains to build multimodal ageotype models. The candidate will also collaborate closely with imaging teams on pipeline harmonization and cross-site analyses. This position offers an opportunity to work at the intersection of primate neuroimaging and molecular aging biology using a uniquely well-powered and phenotypically rich cohort.

Duties and Responsibilities

Neuroimaging Data Acquisition and Processing

• Coordinate with Penn imaging core staff to establish and optimize ex vivo structural MRI acquisition protocols for fixed macaque brain hemispheres on the 7T scanner, including sequence selection, coil configuration, and specimen positioning.
• Develop and maintain automated and manual quality-control procedures for raw MRI data, including measures of signal-to-noise ratio, geometric distortion, and scan completeness.
• Develop and apply pipelines for volumetric segmentation and morphometric characterization of cortical and subcortical regions, adapting FreeSurfer, ANTs, FSL, or equivalent tools for ex vivo fixed-tissue macaque data.
• Register ex vivo brain images to macaque brain atlases, such as D99 or INIA19, generate region-of-interest parcellations, and validate registration accuracy using histological landmarks when available.
• Quantify anatomical markers of brain aging, including regional gray matter volume, cortical myelination, white matter tract integrity from diffusion-weighted imaging, and morphological features associated with cellular aging and neurodegeneration.

Integrative Molecular Analyses of Brain Tissue

• Lead quality control, normalization, and analysis of bulk RNA-seq data from brain regions, including FASTQ-to-count workflows and correction for batch effects, tissue-specific confounders, and cross-tissue variation.
• Analyze brain-tissue DNA methylation data, including development and validation of epigenetic clock models, identification of differentially methylated regions, and comparison of epigenetic aging rates across regions.
• Evaluate and apply single-nucleus or spatial transcriptomics data when available, integrating cell-type-specific aging signatures with regional imaging phenotypes.
• Develop statistical models of age-associated molecular signatures and connect them to neuroimaging measures from the same individuals.
• Collaborate with consortium institutions to integrate brain-derived molecular data with multi-omics datasets.

Multidomain Integration and Ageotype Modeling

• Integrate neuroimaging and molecular measures with physiological, physical-aging, social-network, behavioral, and cognitive data collected from the same CayoBank individuals.
• Contribute to multidomain ageotype models using latent-variable, clustering, and dimensionality-reduction approaches.
• Build and test predictive models linking brain-aging metrics to health and survival outcomes using long-term demographic data from the Cayo Santiago population.

Collaboration, Reproducibility, and Communication

• Align acquisition protocols, atlas choices, parcellation schemes, and quality-control standards with neuroimaging collaborators across sites.
• Coordinate with the CayoHub data-management team to deposit processed imaging and molecular data in formats that meet consortium standards.
• Participate in multi-institutional data working groups and help establish shared analysis standards.
• Develop and maintain documented, reproducible analysis pipelines, preferably using Snakemake or Nextflow, and contribute code to the project GitHub repository.
• Lead manuscripts and presentations on neuroimaging and brain molecular aging findings; contribute to cross-domain ageotype and mortality analyses.
• Contribute to NIH progress reports and grant renewals and assist in mentoring research technicians in neuroanatomical imaging and molecular data processing.

Qualifications

• PhD in neuroscience, neuroimaging, cognitive neuroscience, genomics, computational biology, or a closely related field.
• Strong experience in structural MRI analysis, including volumetric segmentation and morphometry using FreeSurfer, ANTs, FSL, or equivalent tools.
• Experience analyzing next-generation sequencing data, including RNA-seq or DNA methylation data.
• Proficiency in scripting and statistical analysis using Python, R, Bash, or similar tools.
• Experience developing or adapting analysis pipelines for complex or nonstandard datasets.
• Strong organizational skills and the ability to manage large, heterogeneous datasets in a collaborative, multisite project.
• A record of peer-reviewed publications.

Preferred Qualifications

• Experience with ex vivo, postmortem, or high-field MRI at 7T or above.
• Experience with nonhuman primate neuroimaging or neuroanatomy.
• Familiarity with macaque brain atlases, including D99, INIA19, or equivalent resources.
• Experience with single-nucleus or spatial transcriptomics.
• Experience integrating imaging data with molecular, behavioral, or physiological datasets from the same individuals.
• Familiarity with epigenetic clocks or hallmarks-of-aging frameworks.
• Familiarity with Snakemake, Nextflow, Git, and GitHub.
• Experience participating in a large, multi-institutional research consortium.

Application Instructions

Applicants should submit the following materials through Interfolio:

• Cover letter describing relevant research experience, current and future research interests, and desired start date.
• Curriculum vitae, including a list of publications.
• Contact information for three professional references.

Review of applications will continue until the position is filled.

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.