Institution: Morgan State University, Baltimore, MD, USA
Position Overview
We are seeking a highly motivated and innovative Postdoctoral Fellow to contribute to the computational and statistical analysis of high-dimensional multi-modal spatial data. The successful candidate will develop and apply advanced statistical models to integrate spatial transcriptomics, clinical neuroimaging, and multiplexed tissue imaging datasets. You will play a critical role in bridging the gap between macro-scale brain imaging and cellular-level spatial omics.
Key Responsibilities
* Data Analysis & Pipeline Development: Lead the statistical analysis of spatial transcriptomics data (e.g., 10x Visium, Xenium, or MERFISH) and highly multiplexed imaging data (e.g., CODEX).
* Multi-Modal Brain Mapping: Process and analyze neuroimaging datasets (e.g., structural MRI, fMRI, or PET) and integrate these macro-scale clinical images with micro-scale spatial multi-omics to build multiscale models of brain tissue.
* Algorithm & Method Development: Design and implement novel statistical and machine learning methods for spatial domain identification, image segmentation, and cross-modality data alignment.
* Collaboration: Work closely with experimentalists and radiologists to guide experimental design, ensure data quality, and iterate on analytical approaches.
* Scientific Communication: Prepare high-impact manuscripts, present findings at national/international conferences, and assist in drafting computational sections for grant proposals.
Required Qualifications
* Education: Ph.D. in Applied Mathematics, Mathematical Biology, Biostatistics, Bioinformatics, Neuroinformatics, Data Science, or a related quantitative field.
* Statistical Expertise: Strong foundation in statistical modeling, hypothesis testing, and spatial statistics.
* Domain Experience: Proven hands-on experience analyzing spatial transcriptomics datasets, quantitative imaging sciences, and/or neuroimaging data.
* Programming Skills: High proficiency in R and/or Python. Experience with relevant computational libraries (e.g., Seurat, Squidpy, SpatialExperiment).
* Version Control & Compute: Experience with Git/GitHub and working in high-performance computing (HPC) or cloud environments.
* Communication: Excellent written and oral communication skills, with a track record of peer-reviewed publications.
Preferred Qualifications
* Proficiency with standard neuroimaging analysis software and pipelines (e.g., FSL, FreeSurfer, AFNI, SPM, or ANTs).
* Experience with deep learning and computer vision techniques applied to biological or medical images (e.g., medical image registration, cell segmentation).
* Strong background in neuroanatomy, neurobiology, or cognitive neuroscience.
Contact: Send me your CV to Pilhwa Lee, Pilhwa.lee@morgan.edu
