Computational Microscopy Imaging University of Central Florida in United States

PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field.

PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field.

This Postdoctoral Associate will join the Computational Microscopy Imaging Lab (CMIL), led by Dr. Pinaki Sarder, and contribute to a federally funded R01 initiative focused on the integration of spatial omics, transcriptomics, and histology data. The role emphasizes computational analysis of single-cell RNA sequencing data and cutting-edge spatial omics data generated using technologies such as 10X Visium and Xenium. The researcher will lead efforts in integrating multi-modal biomedical data with histological and clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A strong publication record and background in computational biology, molecular omics, and AI are essential.

Spatial Omics Data Processing and Analysis

- Analyze spatial transcriptomics data using platforms such as 10X Visium and Xenium.

- Perform quality control, normalization, spatial clustering, and feature extraction.

- Apply tools for spatial gene expression visualization and interpretation.

Single-Cell RNA-Seq Data Integration

- Process and analyze single-cell RNA sequencing data to support integration with other modalities.

- Conduct clustering, annotation, and alignment with spatial and histological data.

- Assist with incorporating scRNA-seq results into multi-modal pipelines.

Multi-Modal Data Integration and Modeling

- Develop and implement computational workflows for integrating omics, histology, and clinical data.

- Apply machine learning and foundational modeling to support predictive or exploratory analyses.

- Collaborate with interdisciplinary teams to refine multi-modal pipelines.

Scientific Writing and Publications

- Lead or co-author research manuscripts derived from spatial omics and integration analyses.

- Prepare figures, methods, and documentation for publication in peer-reviewed journals.

- Support grant progress reports and contribute to collaborative manuscript efforts.

Collaboration and Reporting

- Participate in research meetings, cross-institution collaborations, and project planning.

- Document analysis pipelines and maintain clear records of research activities.

- Communicate project progress and key findings to the PI and collaborators.

Mentorship and Junior Staff Support

- Guide junior analysts, students, or interns on tools, tasks, and workflow execution.

- Assist with onboarding and ensure alignment with lab goals and project deliverables.

- Offer informal mentoring to promote skill development and consistency in data handling.

$62,232 - $75,564

PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field.

Demonstrated experience in spatial omics data analysis (e.g., 10X Visium, Xenium)

Proficiency with single-cell RNA-seq tools and workflows (e.g., Seurat, Scanpy)

Knowledge of machine learning or foundational modeling applied to biomedical data

Strong publication record in computational biology, systems biology, or AI for healthcare

Experience in high-dimensional data integration and reproducible workflow development

Please attach curriculum vitae.

Final candidate will be required to provide official transcript to the hiring department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an education institution outside of the United States are required to be evaluated by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/ .

The University of Florida is an equal opportunity institution dedicated to building a broadly diverse and inclusive faculty and staff.

Application must be submitted by 11:55 p.m. (ET) of the posting end date.