Research Technician (Term, Full-Time)

The Department of Cell and Developmental Biology is a vibrant interdisciplinary environment for cutting-edge research over a scale that spans seven powers of ten from single molecules to whole organisms. The difference between a test tube and a cell is spatio-temporal organization and we study molecular cellular and tissue organization in many of the laboratories within our department seeking insights into fundamental biological questions and human disease. We are a highly interactive and collaborative community supported by outstanding core facilities and a top-ranked developmental biology program. Recent faculty recruits are advancing areas such as super-resolution imaging of cell migration single-molecule analysis of cytoskeletal dynamics systems biology of intestinal epithelia stem cell biology and spatially resolved approaches to understanding tissue architecture and disease. This environment provides an ideal setting for interdisciplinary research at the interface of imaging computation and cancer biology.

Position Summary:

This is a Term position.

The Research Technician will be a member of the Lau Lab in the Department of Cell and Developmental Biology at Vanderbilt University. This position provides critical technical support with a primary emphasis on computational analysis to study three-dimensional (3D) tumor biology in colorectal cancer. The primary responsibility of this role is to develop and implement advanced computational pipelines to reconstruct and analyze 3D tumor architecture from multimodal imaging platforms including holotomography. The Research Technician will integrate diverse data types-such as label-free imaging multiplex imaging and spatial datasets to generate high-resolution 3D representations of tumor tissues and quantify structural features relevant to tumor-immune interactions. A key focus of this work is to characterize the spatial organization of the tumor microenvironment including immune cell localization stromal compartmentalization extracellular matrix (ECM) architecture and glandular topology.

The Research Technician will develop and apply computational methods for image registration segmentation and 3D reconstruction as well as quantitative spatial analysis of features such as immune-tumor accessibility stromal barrier continuity and invasive tumor architecture. This includes implementing machine learning and AI-based approaches (e.g. deep learning models generative modeling and graph-based analysis) to infer continuous tissue structures and identify biologically meaningful patterns from large-scale imaging datasets.

The Research Technician will also support experimental studies involving CRISPR-based genome engineering. This includes assisting in the development of engineered colorectal cancer cell lines to modulate the expression of genes associated with tumor progression. These engineered models along with syngeneic mouse systems will be used to investigate tumor-microenvironment interactions and mechanisms of immune regulation.

Key Functions and Expected Performance:

• Develop and implement computational pipelines for multimodal 3D imaging data (e.g. holotomography)
• Perform image processing registration segmentation and quantitative spatial analysis of tumor architecture
• Apply machine learning approaches (e.g. deep learning generative models graph-based methods) for 3D reconstruction and feature extraction Integrate multimodal datasets (imaging spatial profiling and molecular data) to study tumor microenvironment organization
• Support imaging workflows and basic molecular biology (e.g. PCR) if needed
• Assist with CRISPR-based cell line development and mouse tissue collection for downstream analysis
• Collaborate with lab members on computational and experimental workflows

Supervisory Relationships:

This position does not have supervisory responsibility this position reports administratively and functionally to the PI Ken Lau.

Education and Certifications:

• Bachelors in a biology field is strongly preferred.

Experience and Skills:

• Computational skills are strongly preferred.
• Lab experience is strongly preferred.