News & Updates

HDR opportunities

Are you looking for an Honours, Masters, or PhD project in Single Cell or Spatial-Omics? We are seeking talented individuals to join our group. We can tailor projects to suit your interests and desired skill-set. Some project ideas:

Bioinformatics: Single Cell and Spatial-Omics pipeline development

The field of Single Cell and Spatial-Omics is fast moving with significant technology improvements released frequently from many different competitors. Our lab is testing the limits of these emerging technologies and developing new protocols to enable novel analyses. This often requires the development of new bioinformatics tools and pipelines to support the new protocol, either in terms of data preprocessing or analysis. Furthermore, the software supporting these platforms is minimal with ample opportunity for expansion. Our current interests are:

Pipeline to support preprocessing for custom single-cell libraries. We have several projects that extend the capabilities of technologies such as 10X’s Flex gene expression probes. This project would lead the development and validation of a preprocessing pipeline to support these new protocols.

Improved algorithms for Spatial-Omics analysis. Spatial transcriptomics has seen increased dimensions as well as order of magnitude increase in the volume of data collected per experiment. The current analysis algorithms are still in their infancy and there are many opportunities for improved preprocessing and analysis methods. We are currently interested in improved cell segmentation and segmentation-free analyses, spatially-informed cell clustering and typing, and analysis methods for higher dimensions. 

Experience with Linux command line and programming in R or Python will be helpful but not required.

Combined gene expression profiling and mutant genotyping of cancer cell lines

We recently developed the snPATHO-seq protocol for gene expression profiling of tissue from Formalin-Fixed, Paraffin-Embedded (FFPE) clinical histology samples. We are looking to expand this probed-based method to identify cancer mutations, allowing users to generate two disparate but crucial datasets from the one simple and cost-effective assay. This has significant benefits both for patient outcomes as well as research applications looking at cancer heterogeneity and their cell signalling and pathway response. The ability to process FFPE samples is important as it enables researchers to access the millions of preserved historical samples across the world's clinical archives. This project would be suitable for an Honours or Masters student looking to complete a combined wet-lab and bioinformatics project.