Scientist, Developing Spatial RNA Sequencing Technologies in Tissues (GIS)

Spatial RNA technologies are transforming how we study gene expression, RNA regulation and cellular function in intact cells and tissues. 3D-resolved imaging-based technologies, such as STARmap PLUS, RIBOmap and TEMPOmap, enable highly multiplexed in situ profiling of RNA translation and dynamics. The Laboratory of Spatial RNA Biology & Technology has established track record in the spatial technology development. Together, these methods provide spatial and temporal views of the RNA life cycle, including transcription, localization, translation and degradation, at single-cell and subcellular resolution.

This project will focus on building new biotechnology tools based on our previous works. Specifically, we aim to build an in vivo RNA imaging and sequencing platform to spatially track RNA dynamics across cell types in intact tissues. The project will integrate metabolic labeling, click chemistry, highly multiplexed in situ sequencing, confocal imaging, and computational image analysis to map sequential RNA transcription in native tissue contexts. The long-term goal is to reconstruct temporal trajectories of RNA regulation, cell-state transitions, and tissue development in four dimensions.

Job description

We are looking for a highly motivated scientist to help develop and apply next-generation spatial omics technologies. The successful candidate will contribute to both experimental technology development and computational pipeline construction.

The candidate will be expected to:

• Develop and optimize wet-lab protocols for STARmap, RIBOmap, TEMPOmap, and other RNA imaging technologies
• Design and validate oligonucleotide probe libraries
• Perform sample preparation using cultured cells, organoids, and mammalian or human tissue samples
• Perform basic animal work and animal injection procedures, including handling, tissue collection, and in vivo delivery of metabolic labels or experimental reagents, in accordance with institutional animal protocols
• Operate and optimize high-resolution fluorescence and confocal microscopy workflows for cyclic imaging-based in situ sequencing
• Build and maintain computational pipelines for image preprocessing
• Analyze spatial transcriptomic, translatomic, and nascent RNA datasets using Python/R-based tools and actively work with AI tools
• Work closely with lab members to apply these technologies to biological questions in development, aging, immune function, and tissue organization

We offer

• A fully funded position with an internationally competitive salary
• The opportunity to help build a new research program at the interface of spatial omics technology, RNA biology, imaging, and computational genomics
• Professional development opportunities, including support for publications, fellowship and grant applications, conferences, and workshops
• Access to state-of-the-art research infrastructure, including advanced microscopy, sequencing, and computational resources
• A dynamic, interdisciplinary, and collaborative research environment
• The position is initially offered for one year, with the possibility of renewal

How to apply

We look forward to receiving your application with the following documents:

• Cover letter
• CV with a list of publications
• Contact information for three references