Research Officer, Spatial RNA Biology & Technology

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of Spatial RNA Biology & Technology founded by incoming Principal Investigator Rena Ren, which aims to develop cutting-edge RNA technology to understand post-transcriptional RNA dynamics in early development and aging tissues. We are forming a group of biotechnology developers, molecular biologists and computational scientists to advance our understanding of RNA using imaging and genomic tools. Located in the heart of Singapore’s thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore’s vibrant research ecosystem and strong support for innovation.

Project background

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, RIBOmap and TEMPOmap, enable highly multiplexed in situ profiling of RNA translation and dynamics. 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 robust computational pipelines for processing and analyzing high-dimensional spatial datasets and developing new analytical framework for them. The work will involve image preprocessing and registration, spot-finding, single-cell quantification and downstream single-cell and subcellular analysis.

Job duties and responsibilities

We invite highly motivated candidates with strong computational biology, bioimage analysis, computer science or bioinformatics backgrounds to join a new startup lab focused on spatial RNA technology and biology. Your work will be central to establishing and advancing our computational pipelines and algorithms for imaging-based spatial omics data.

The position will likely involve developing and optimizing image-processing workflows for highly multiplexed in situ sequencing data. The candidate will also help build downstream analysis workflows for spatial gene expression analysis, RNA translational efficiency analysis, RNA kinetic modeling and multimodal integration.

The successful candidate will work closely with wet-lab scientists to troubleshoot experiments, evaluate data quality, improve computational performance and translate raw microscopy images into biologically interpretable datasets.

Job requirements

Bachelor’s, Master’s in Computational Biology, Bioinformatics, Chemical Biology, Computer Science, Biomedical Engineering, or a related field

Strong experience of programming in Python, R and working with AI tools

Experience with or keen interest in image processing, microscopy image analysis, computer vision or spatial omics data analysis

Experience with bioinformatics, single-cell or spatial transcriptomics analysis tools such as Scanpy, Seurat, Squidpy or related packages

Comfortable working with large imaging datasets and high-performance computing environments

Keen interest in spatial genomics and transcriptomics, computational pipeline building and mathematical modeling in RNA kinetics

Research Officer, Spatial RNA Biology & Technology

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of Spatial RNA Biology & Technology founded by incoming Principal Investigator Rena Ren, which aims to develop cutting-edge RNA technology to understand post-transcriptional RNA dynamics in early development and aging tissues. We are forming a group of biotechnology developers, molecular biologists and computational scientists to advance our understanding of RNA using imaging and genomic tools. Located in the heart of Singapore’s thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore’s vibrant research ecosystem and strong support for innovation.

Project background

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, RIBOmap and TEMPOmap, enable highly multiplexed in situ profiling of RNA translation and dynamics. 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 robust computational pipelines for processing and analyzing high-dimensional spatial datasets and developing new analytical framework for them. The work will involve image preprocessing and registration, spot-finding, single-cell quantification and downstream single-cell and subcellular analysis.

Job duties and responsibilities

We invite highly motivated candidates with strong computational biology, bioimage analysis, computer science or bioinformatics backgrounds to join a new startup lab focused on spatial RNA technology and biology. Your work will be central to establishing and advancing our computational pipelines and algorithms for imaging-based spatial omics data.

The position will likely involve developing and optimizing image-processing workflows for highly multiplexed in situ sequencing data. The candidate will also help build downstream analysis workflows for spatial gene expression analysis, RNA translational efficiency analysis, RNA kinetic modeling and multimodal integration.

The successful candidate will work closely with wet-lab scientists to troubleshoot experiments, evaluate data quality, improve computational performance and translate raw microscopy images into biologically interpretable datasets.

Job requirements

Bachelor’s, Master’s in Computational Biology, Bioinformatics, Chemical Biology, Computer Science, Biomedical Engineering, or a related field

Strong experience of programming in Python, R and working with AI tools

Experience with or keen interest in image processing, microscopy image analysis, computer vision or spatial omics data analysis

Experience with bioinformatics, single-cell or spatial transcriptomics analysis tools such as Scanpy, Seurat, Squidpy or related packages

Comfortable working with large imaging datasets and high-performance computing environments

Keen interest in spatial genomics and transcriptomics, computational pipeline building and mathematical modeling in RNA kinetics